v0.36.5: Duration arithmetic support

Duration enum now supports multiplication, division, and addition
so expressions like `Duration.WHOLE * 2` work instead of raising TypeError.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

CHANGELOG.md

@@ -2,6 +2,55 @@
 
 All notable changes to PyTheory are documented here.
 
+## 0.36.5
+
+- **Duration arithmetic** — `Duration.WHOLE * 2`, `Duration.HALF + Duration.QUARTER`,
+  division, and reverse multiply all work now (previously raised TypeError)
+
+## 0.36.3
+
+- **`Part.hold()`** — polyphonic overlap on a single part. Add notes
+  without advancing the beat position so they play simultaneously.
+  Enables: piano sustain, sitar drone under melody, guitar strum texture.
+- **Strum uses hold()** — leading string plays simultaneously with chord,
+  no more timing gaps or choppiness
+- **Improved songs** 1-16: humanize, velocity dynamics, reverb, saxophone
+  for blues
+- **Ctrl-C handling** — clean stop on all playback functions
+- **REPL updates** — strum, roll, bend, temperament, reference commands
+- Song #28 Descent (generative), #29 Pop Rock, #30 Sitar Drone
+- 862 tests
+
+## 0.36.1
+
+- **7 new instrument synths:** pedal steel guitar, theremin, kalimba/thumb
+  piano, steel drum/pan, accordion (musette reeds), didgeridoo (drone +
+  shifting formants), bagpipes (chanter reed)
+- **9 new demo moods** in ``pytheory demo``: Theremin Noir, Caribbean,
+  Accordion Waltz, Kalimba Dreams, Outback Drone, Highland, Nashville
+  Tears, Tabla Fusion
+- Improved existing songs with dedicated instrument synths
+- 41 synth waveforms, 26+ songs, 21 demo moods
+
+## 0.36.0
+
+- **Banjo synth** — steel strings on drum-head body, nasal twang,
+  fast decay with membrane resonance
+- **Mandolin synth** — paired steel strings (natural chorus from
+  doubled courses), bright body resonance
+- **Ukulele synth** — nylon strings, small mid-heavy body, shorter
+  sustain than guitar
+- **Cajón drums** — bass (woody box thump), slap (snare wire buzz),
+  tap (ghost note). 3 patterns: cajon, cajon rumba, cajon folk
+- **Vocal/formant synth** — LF glottal model, 5 Peterson & Barney
+  formant peaks, jitter/shimmer, consonant onsets, per-note lyrics.
+  Presets: vocal, choir
+- **Granular synthesis** — grain cloud engine with scatter, pitch
+  variation, Hanning windows. Presets: granular_pad, granular_texture
+- **Strum sweep** — subtle grace notes before chord hit for natural
+  strum feel on all fretboard instruments
+- Mandola preset, 34 synth waveforms, 26 songs
+
 ## 0.35.0
 
 - **8.5x faster import** — dropped pytuning/sympy, lazy-load scipy.

docs/guide/chords.rst

@@ -322,6 +322,14 @@ against 17 known chord types (triads, 7ths, 9ths, sus, power chords).
    >>> Chord.from_tones("Bb", "D", "F").identify()
    'Bb major'
 
+Enharmonic spellings are fully supported — Cb, Fb, E#, B#, double
+sharps/flats, and unicode symbols (see :doc:`tones` for details):
+
+.. code-block:: pycon
+
+   >>> Chord.from_tones("Cb", "Eb", "Gb").identify()
+   'B minor'
+
 You can also access the root and quality separately:
 
 .. code-block:: pycon

docs/guide/drums.rst

@@ -9,7 +9,7 @@ in Atlanta. Over a dancehall pattern, you're in Kingston. The drums ARE
 the genre -- they tell the listener's body how to move before a single
 melodic note is played.
 
-PyTheory includes a complete drum system -- 27 synthesized percussion
+PyTheory includes a complete drum system -- 51 synthesized percussion
 sounds, 80+ pattern presets across dozens of genres, and 21 fill presets.
 Every sound is generated from waveforms; no samples needed.
 
@@ -91,7 +91,7 @@ The ``DrumSound`` enum maps to General MIDI percussion note numbers:
    >>> DrumSound.CLOSED_HAT.value
    42
 
-All 27 sounds, organized by type:
+All 51 sounds, organized by type:
 
 **Kicks:** KICK (36)
 
@@ -106,7 +106,24 @@ All 27 sounds, organized by type:
 **Percussion:** COWBELL (56), CLAVE (75), SHAKER (70), TAMBOURINE (54),
 CONGA_HIGH (63), CONGA_LOW (64), BONGO_HIGH (60), BONGO_LOW (61),
 TIMBALE_HIGH (65), TIMBALE_LOW (66), AGOGO_HIGH (67), AGOGO_LOW (68),
-GUIRO (73), MARACAS (70)
+GUIRO (73)
+
+**Tabla:** TABLA_NA (86), TABLA_TIN (87), TABLA_GE (88), TABLA_DHA (89),
+TABLA_TIT (90), TABLA_KE (91), TABLA_GE_BEND (108 -- bayan with upward
+pitch bend from palm pressing into the head)
+
+**Dhol:** DHOL_DAGGA (92), DHOL_TILLI (93), DHOL_BOTH (94)
+
+**Dholak:** DHOLAK_GE (95), DHOLAK_NA (96), DHOLAK_TIT (97)
+
+**Mridangam:** MRIDANGAM_THAM (98), MRIDANGAM_NAM (99), MRIDANGAM_DIN (100),
+MRIDANGAM_THA (101)
+
+**Djembe:** DJEMBE_BASS (102), DJEMBE_TONE (103), DJEMBE_SLAP (104)
+
+**Cajón:** CAJON_SLAP (109), CAJON_TAP (110)
+
+**Metal Kit:** METAL_KICK (105), METAL_SNARE (106), METAL_HAT (107)
 
 Drum Synthesis
 --------------
@@ -200,8 +217,8 @@ everything to its essentials. The metal kit adds 3 dedicated sounds
 (double kick, china cymbal, stack) and 4 patterns for extreme metal
 subgenres.
 
-**World Percussion:** tabla, dhol, dholak, mridangam, djembe -- Deep
-traditions from across the globe, each with authentic sound sets and
+**World Percussion:** tabla, dhol, dholak, mridangam, djembe, cajón --
+Deep traditions from across the globe, each with authentic sound sets and
 idiomatic patterns. See the World Percussion section below for details.
 
 **Other:** funk, hip hop, bo diddley, second line, new orleans, waltz,
@@ -330,14 +347,25 @@ most expressive percussion instruments ever created. A single tabla
 player can produce an astonishing range of tones by varying finger
 placement, pressure, and striking technique.
 
-**6 sounds** -- covering the primary tabla strokes (na, tin, tun, ge,
-ke, and ti-ra-ki-ta combinations).
+**7 sounds** -- covering the primary tabla strokes (na, tin, tun, ge,
+dha, ke, tit) plus a bayan pitch bend sound (TABLA_GE_BEND) that
+models the technique of pressing the palm into the bayan head to bend
+the pitch upward.
 
 **7 patterns:** teental (16 beats, the most common taal), jhaptaal
 (10 beats), rupak (7 beats), dadra (6 beats), keherwa (8 beats, folk
 and light classical), tabla solo, and tiri kita (fast ornamental
 pattern).
 
+**5 fills:** tihai (3x crescendo landing on sam), chakkardar (32nd
+triplet cascade into slam), tiri kita (rapid 16th-note dayan burst),
+bayan (deep bass bends showcase), tabla call (dayan/bayan call-and-response).
+
+.. code-block:: python
+
+   score.drums("teental", repeats=4, fill="tihai")
+   score.drums("keherwa", repeats=4, fill="chakkardar")
+
 .. code-block:: python
 
    score = Score("4/4", bpm=80)
@@ -433,6 +461,23 @@ classic triplet-feel gallop rhythm).
    score = Score("4/4", bpm=200)
    score.drums("metal blast", repeats=4)
 
+Cajón
+~~~~~
+
+The cajón is a box-shaped percussion instrument from Peru, now
+ubiquitous in acoustic and unplugged settings worldwide. Players sit
+on the box and strike the front face with their hands.
+
+**2 sounds** -- slap (sharp, snare-like) and tap (bass-like).
+
+**3 patterns:** cajon (basic groove), cajon rumba (flamenco-style rumba),
+and cajon folk (folk/acoustic pattern).
+
+.. code-block:: python
+
+   score = Score("4/4", bpm=100)
+   score.drums("cajon", repeats=4)
+
 MIDI Export
 -----------
 

docs/guide/effects.rst

@@ -841,9 +841,11 @@ processes each section independently:
    lead.arpeggio("Gm", bars=4, pattern="updown", octaves=2)
 
 Any parameter can be automated: ``lowpass``, ``lowpass_q``, ``highpass``,
-``reverb``, ``reverb_decay``, ``delay``, ``delay_time``, ``delay_feedback``,
-``distortion``, ``distortion_drive``, ``chorus``, ``phaser``, ``phaser_rate``,
-``saturation``, ``tremolo_depth``, ``tremolo_rate``, ``volume``.
+``reverb``, ``reverb_decay``, ``reverb_type``, ``delay``, ``delay_time``,
+``delay_feedback``, ``distortion``, ``distortion_drive``, ``chorus``,
+``phaser``, ``phaser_rate``, ``saturation``, ``tremolo_depth``,
+``tremolo_rate``, ``cabinet``, ``cabinet_brightness``, ``analog_drift``,
+``volume``.
 
 LFO Automation
 --------------

docs/guide/playback.rst

@@ -66,6 +66,17 @@ the mix louder and punchier:
        chords.add(Chord.from_symbol(sym), Duration.WHOLE)
    play_score(score)
 
+The render pipeline respects the Score's ``temperament`` and
+``reference_pitch`` settings, so Baroque or microtonal scores play back
+at the correct tuning:
+
+.. code-block:: python
+
+   score = Score("4/4", bpm=80, temperament="meantone", reference_pitch=415.0)
+
+Press **Ctrl+C** at any time during playback to stop — PyTheory catches
+``KeyboardInterrupt`` and stops audio cleanly.
+
 See :doc:`sequencing` for how to build scores and parts.
 
 render_score() -- Headless Rendering
@@ -153,7 +164,7 @@ Play a drum pattern through the speakers:
    play_pattern(Pattern.preset("rock"), repeats=4, bpm=120)
    play_pattern(Pattern.preset("bossa nova"), repeats=4, bpm=140)
 
-See :doc:`drums` for the full list of 58 presets and 21 fills.
+See :doc:`drums` for the full list of 80+ presets and 21 fills.
 
 play_progression() -- Quick Chord Playback
 ------------------------------------------

docs/guide/sequencing.rst

@@ -667,8 +667,16 @@ A Score can use any tuning system and temperament:
    # Just intonation — pure intervals
    score = Score("4/4", bpm=90, temperament="just")
 
-Temperaments: ``"equal"`` (default), ``"pythagorean"``, ``"meantone"``,
-``"just"``.
+The Score constructor accepts these tuning parameters:
+
+- ``system``: Musical system name (default ``"western"``). Any system
+  from :doc:`systems` works — ``"indian"``, ``"shruti"``, ``"maqam"``,
+  ``"carnatic"``, etc. Note strings in ``Part.add()`` are parsed against
+  this system.
+- ``temperament``: Tuning temperament — ``"equal"`` (default),
+  ``"pythagorean"``, ``"meantone"``, ``"just"``.
+- ``reference_pitch``: Concert pitch in Hz (default 440.0). Use 415.0
+  for Baroque tuning, 432.0 for "Verdi tuning", etc.
 
 Custom equal temperaments via the ``TET()`` factory:
 

docs/guide/synths.rst

@@ -1,7 +1,7 @@
 Synthesizers
 ============
 
-PyTheory includes 30 built-in waveforms and 10 ADSR envelope presets.
+PyTheory includes 41 built-in waveforms and 10 ADSR envelope presets.
 Every sound is generated from scratch -- no samples or external audio
 files needed.
 
@@ -390,11 +390,11 @@ Dedicated Instrument Synths
 --------------------------
 
 Beyond the classic and physical modeling waveforms, PyTheory includes
-17 dedicated instrument synths. Each one uses tailored synthesis
+31 dedicated instrument synths. Each one uses tailored synthesis
 techniques -- additive harmonics, formant shaping, body resonance
 modeling, and specialized envelopes -- to capture the character of a
 specific acoustic instrument. These are the waveforms that bring the
-total count to 30.
+total count to 41.
 
 Piano Synth
 ~~~~~~~~~~~
@@ -558,6 +558,107 @@ mids, reed buzz, and brass body warmth. Four presets: ``saxophone``,
 
    sax = score.part("sax", instrument="tenor_sax")
 
+Pedal Steel Synth
+~~~~~~~~~~~~~~~~~
+
+The Nashville crying sound — singing harmonics with slow vibrato
+and long sustain. Pairs naturally with spring reverb.
+
+.. code-block:: python
+
+   steel = score.part("steel", instrument="pedal_steel")
+
+Theremin Synth
+~~~~~~~~~~~~~~
+
+Pure sine with natural hand wobble — the eerie sci-fi sound.
+Best used with legato and glide for continuous pitch.
+
+.. code-block:: python
+
+   theremin = score.part("theremin", instrument="theremin")
+
+Kalimba Synth
+~~~~~~~~~~~~~
+
+Metal tines on a wooden body. Bright, bell-like attack with
+inharmonic overtones (modes at 1x, 2.92x, 5.4x).
+
+.. code-block:: python
+
+   kalimba = score.part("kalimba", instrument="kalimba")
+
+Steel Drum Synth
+~~~~~~~~~~~~~~~~
+
+Hammered metal pan with bright, ringing, tropical character.
+Inharmonic partials at 2.0x, 3.01x, 4.1x, 5.3x.
+
+.. code-block:: python
+
+   pan = score.part("pan", instrument="steel_drum")
+
+Accordion Synth
+~~~~~~~~~~~~~~~
+
+Musette-tuned doubled reeds — two slightly detuned reed sets
+create natural beating. Bellows pressure swell modulates amplitude.
+
+.. code-block:: python
+
+   acc = score.part("acc", instrument="accordion")
+
+Didgeridoo Synth
+~~~~~~~~~~~~~~~~
+
+Deep cylindrical drone with shifting formant overtones. The
+overtone singing effect sweeps a resonant peak between 500-1500Hz.
+Best with cave reverb.
+
+.. code-block:: python
+
+   didg = score.part("didg", instrument="didgeridoo")
+
+Bagpipe Synth
+~~~~~~~~~~~~~
+
+Bright chanter reed with constant bag pressure. All harmonics
+peaked around 3-7 (the piercing brightness). No dynamics — always ff.
+
+.. code-block:: python
+
+   pipes = score.part("pipes", instrument="bagpipe")
+
+Banjo Synth
+~~~~~~~~~~~
+
+Steel strings on a drum-head membrane body. The membrane gives
+nasal, ringy resonance with faster decay than guitar.
+
+.. code-block:: python
+
+   banjo = score.part("banjo", instrument="banjo")
+
+Mandolin Synth
+~~~~~~~~~~~~~~
+
+Paired steel strings in 4 courses — natural chorus from the
+doubled unison strings. Bright, ringing, fast attack.
+
+.. code-block:: python
+
+   mando = score.part("mando", instrument="mandolin")
+
+Ukulele Synth
+~~~~~~~~~~~~~
+
+Nylon strings on a small body. Mid-heavy resonance (no deep bass),
+softer attack than guitar, shorter sustain.
+
+.. code-block:: python
+
+   uke = score.part("uke", instrument="ukulele")
+
 Granular Synth
 ~~~~~~~~~~~~~~
 
@@ -614,7 +715,7 @@ Instrument Presets
 ------------------
 
 Instead of choosing synth + envelope + effects manually, use an
-instrument preset — 40+ predefined combinations that approximate real
+instrument preset — 60+ predefined combinations that approximate real
 instruments:
 
 .. code-block:: python
@@ -627,20 +728,28 @@ instruments:
 
 Available instruments:
 
-**Keys**: piano, electric_piano, organ, harpsichord, celesta, music_box
+**Keys**: piano, electric_piano, organ, harpsichord, celesta, music_box,
+accordion
 
 **Strings**: violin, viola, cello, contrabass, string_ensemble
 
-**Woodwinds**: flute, clarinet, oboe, bassoon
+**Woodwinds**: flute, clarinet, oboe, bassoon, saxophone, alto_sax,
+tenor_sax, bari_sax
 
 **Brass**: trumpet, trombone, french_horn, tuba, brass_ensemble
 
-**Plucked**: acoustic_guitar, electric_guitar, distorted_guitar,
-bass_guitar, upright_bass, harp, sitar, koto
+**Plucked**: acoustic_guitar, electric_guitar, clean_guitar, crunch_guitar,
+distorted_guitar, orange_crunch, metal_guitar, bass_guitar, upright_bass,
+harp, sitar, koto, banjo, mandolin, mandola, ukulele
 
-**Synth**: synth_lead, synth_pad, synth_bass, acid_bass, 808_bass
+**World/Exotic**: pedal_steel, theremin, kalimba, steel_drum, didgeridoo,
+bagpipe
 
-**Percussion**: vibraphone, marimba, xylophone, glockenspiel, tubular_bells
+**Synth**: synth_lead, synth_pad, synth_bass, acid_bass, 808_bass,
+granular_pad, granular_texture, vocal, choir
+
+**Percussion**: vibraphone, marimba, xylophone, glockenspiel, tubular_bells,
+timpani
 
 Explicit kwargs override preset defaults:
 

docs/guide/systems.rst

@@ -1,10 +1,11 @@
 Musical Systems
 ===============
 
-PyTheory supports **six musical systems**, each with its own tone names,
-scale patterns, and centuries of tradition behind them. Every system
-maps onto the same 12-tone equal temperament backbone, so you can
-compare scales across cultures and even combine them in your own music.
+PyTheory supports **16 musical systems** — 6 core systems mapped onto
+12-tone equal temperament, plus 10 microtonal systems with their own
+native tunings. The core systems let you compare scales across cultures;
+the microtonal systems go beyond 12-TET into genuinely different pitch
+universes.
 
 Western
 -------
@@ -271,4 +272,117 @@ produce the same pitches:
    >>> do4.frequency
    261.6255653005986
 
+Microtonal Systems
+------------------
+
+Beyond the six 12-TET core systems, PyTheory includes 10 microtonal
+systems that use their own native tunings — more notes per octave,
+just intonation ratios, or entirely alien pitch structures.
+
+Shruti (22 tones per octave)
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+The Indian 22-shruti system divides the octave into 22 unequal steps
+using just intonation ratios. These microtonal inflections are what
+give classical Indian music its characteristic expressiveness — pitches
+that fall "between the cracks" of the piano.
+
+.. code-block:: python
+
+   score = Score("4/4", bpm=75, system="shruti")
+
+Maqam (24 tones per octave)
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+The Arabic 24-tone system adds Zalzalian quarter-tone intervals
+(derived from just intonation ratios of 11 and 13) to the standard
+12 tones. These "neutral" intervals — halfway between major and minor —
+are the soul of maqam music.
+
+.. code-block:: python
+
+   score = Score("4/4", bpm=90, system="maqam")
+
+Slendro (5-TET)
+~~~~~~~~~~~~~~~~
+
+The Javanese slendro scale — 5 equal divisions of the octave. Each
+step is 240 cents, wider than any Western interval. Ethereal and
+floating.
+
+Pelog (9-TET)
+~~~~~~~~~~~~~
+
+Approximation of the Javanese pelog tuning as 9 equal divisions of
+the octave.
+
+Thai (7-TET)
+~~~~~~~~~~~~~
+
+Thai classical music divides the octave into 7 equal steps of ~171
+cents each — every interval is the same size.
+
+Makam (53-TET)
+~~~~~~~~~~~~~~
+
+Turkish makam music uses 53 equal divisions of the octave — fine
+enough to approximate virtually any just interval. The system that
+underlies Ottoman classical music.
+
+Carnatic (72-TET)
+~~~~~~~~~~~~~~~~~
+
+South Indian Carnatic music theory describes 72 melakarta ragas.
+The 72-TET system provides enough resolution to represent all the
+microtonal inflections of Carnatic practice.
+
+19-TET and 31-TET
+~~~~~~~~~~~~~~~~~~
+
+Extended equal temperaments that offer better approximations of
+just intonation intervals than 12-TET. 19-TET has excellent major
+thirds; 31-TET closely matches quarter-comma meantone.
+
+.. code-block:: python
+
+   score = Score("4/4", bpm=100, system="19-tet")
+
+Bohlen-Pierce (13 equal divisions of the tritave)
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+A genuinely alien tuning system — 13 equal divisions of the
+**tritave** (3:1 ratio) instead of the octave (2:1). No octaves, no
+fifths, built on 3:5:7 harmonics. Used by experimental composers.
+
+.. code-block:: python
+
+   score = Score("4/4", bpm=100, system="bohlen-pierce")
+
+The TET() Factory
+~~~~~~~~~~~~~~~~~
+
+Create any equal temperament on the fly with the ``TET()`` factory:
+
+.. code-block:: python
+
+   from pytheory import TET
+
+   edo19 = TET(19)   # 19-tone equal temperament
+   edo31 = TET(31)   # 31-tone equal temperament
+   score = Score("4/4", bpm=100, system=edo19)
+
+Tone names in custom TET systems are integers (0, 1, 2, ..., n-1).
+
+System.tone() Method
+~~~~~~~~~~~~~~~~~~~~
+
+Any system can create a Tone directly:
+
+.. code-block:: python
+
+   from pytheory import SYSTEMS
+
+   western = SYSTEMS["western"]
+   c4 = western.tone("C", octave=4)
+
 Music is universal, but every culture hears it differently. These systems are different maps of the same territory -- explore one you've never played in before and see what you find.

docs/guide/tones.rst

@@ -357,6 +357,45 @@ every tone knows its enharmonic spelling:
    >>> Tone.from_string("C4", system="western").enharmonic is None
    True
 
+Extended Enharmonics
+~~~~~~~~~~~~~~~~~~~~
+
+PyTheory supports the full range of enharmonic spellings used in real
+music theory:
+
+- **Cb** and **Fb** — musically valid flats (Cb = B, Fb = E)
+- **E#** and **B#** — musically valid sharps (E# = F, B# = C)
+- **Double sharps** (``##`` or ``x``) — e.g. F## = G
+- **Double flats** (``bb``) — e.g. Dbb = C
+- **Unicode symbols** — ``♯`` (sharp), ``♭`` (flat), ``𝄪`` (double sharp),
+  ``𝄫`` (double flat) are all recognized and normalized to ASCII
+
+.. code-block:: pycon
+
+   >>> Tone.from_string("Cb4")   # resolves to B3 (octave boundary fix)
+   <Tone B3>
+   >>> Tone.from_string("B#4")   # resolves to C5 (octave boundary fix)
+   <Tone C5>
+   >>> Tone.from_string("E#4")   # resolves to F4
+   <Tone F4>
+   >>> Tone.from_string("Fb4")   # resolves to E4
+   <Tone E4>
+
+The octave boundary is correctly handled: B# crosses up to the next
+octave (B#4 = C5), and Cb crosses down (Cb4 = B3), matching standard
+scientific pitch notation where the octave number increments at C.
+
+Tone Validation
+~~~~~~~~~~~~~~~
+
+Tones are validated on construction — if a tone name is not recognized
+in its system, a ``ValueError`` is raised:
+
+.. code-block:: pycon
+
+   >>> Tone.from_string("X4")   # not a valid tone name
+   ValueError: ...
+
 The Circle of Fifths
 --------------------
 

docs/index.rst

@@ -18,8 +18,8 @@ Theory
 ------
 
 The theory layer works everywhere Python runs — no audio setup needed.
-Tones, scales, chords, keys, intervals, harmony, 6 musical systems,
-25 instruments:
+Tones, scales, chords, keys, intervals, harmony, 16 musical systems,
+60+ instruments:
 
 .. code-block:: pycon
 
@@ -72,25 +72,29 @@ every time::
 What's Inside
 -------------
 
-- **Theory** — tones, scales (40+ across 6 systems), chords (17 types),
+- **Theory** — tones, scales (40+ across 16 systems), chords (17 types),
   keys, Roman numeral analysis, figured bass, pitch class sets (Forte
-  numbers), scale recommendation, modulation, voice leading
+  numbers), scale recommendation, modulation, voice leading, enharmonic
+  support (Cb, Fb, E#, B#, double sharps/flats, unicode symbols)
 - **Sequencing** — Score, Parts, arpeggiator, legato/glide, velocity,
-  swing, humanize, tempo changes, song sections with repeat
-- **Synthesis** — 30 waveforms (including Karplus-Strong pluck, Hammond organ,
-  bowed string, and 14 dedicated instrument synths), 10 envelopes, 40+
-  instrument presets, configurable FM, sub-oscillator, noise layer, filter
-  envelope, velocity-to-brightness, analog oscillator drift, detune, stereo
-  pan/spread, strumming, 80+ drum patterns (stereo panned, including world
-  percussion), 21 fills
+  swing, humanize, tempo changes, song sections with repeat, strumming,
+  pitch bends (3 types), rolls, tuning systems (TET factory, 4
+  temperaments, reference_pitch)
+- **Synthesis** — 41 waveforms (including Karplus-Strong pluck, Hammond organ,
+  bowed string, granular, vocal/formant, and 31 dedicated instrument synths),
+  10 envelopes, 60+ instrument presets, configurable FM, sub-oscillator,
+  noise layer, filter envelope, velocity-to-brightness, analog oscillator
+  drift, detune, stereo pan/spread, 80+ drum patterns (stereo panned,
+  including world percussion and cajón), 21 fills, 11 microtonal systems
 - **Effects** — reverb (algorithmic + 7 convolution IRs, stereo), delay,
-  lowpass/highpass (with resonance), distortion, cabinet simulation,
+  lowpass/highpass (with resonance), distortion, guitar cabinet simulation,
   saturation, chorus, phaser, tremolo, analog drift, sidechain compression,
   automation, LFOs. Master bus compressor/limiter
-- **Instruments** — 49 presets with fingering generation, guitar strumming,
-  pitch bends
+- **Instruments** — 60+ presets with fingering generation, guitar strumming,
+  pitch bends, note choking
 - **Output** — stereo playback, WAV export, MIDI import/export
-- **Interface** — REPL with tab completion, CLI (15 commands), ``pytheory demo``
+- **Interface** — REPL with tab completion, CLI (15 commands), ``pytheory demo``,
+  KeyboardInterrupt handling for clean stop
 - **AI-friendly** — Claude Code can compose
   and play music through PyTheory from natural language
 

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "pytheory"
-version = "0.35.1"
+version = "0.36.5"
 description = "Music Theory for Humans"
 readme = "README.md"
 license = "MIT"

pytheory/__init__.py

@@ -1,6 +1,6 @@
 """PyTheory: Music Theory for Humans."""
 
-__version__ = "0.35.1"
+__version__ = "0.36.5"
 
 from .tones import Tone, Interval
 from .systems import System, SYSTEMS, TET

pytheory/cli.py

@@ -299,6 +299,54 @@ def cmd_demo(args):
          "lead": ("trumpet_synth", "bowed", 0.3, 0.2),
          "pad": ("piano_synth", "none", -0.2),
          "bass_lp": 600, "reverb_type": "plate"},
+        {"name": "Theremin Noir", "key": ("A", "minor"), "drums": "hip hop",
+         "fill": "rock", "bpm": 85,
+         "prog": ("i", "iv", "V", "i"),
+         "lead": ("theremin_synth", "pad", 0.4, 0.0),
+         "pad": ("strings_synth", "pad", 0.0),
+         "bass_lp": 300, "reverb_type": "cave"},
+        {"name": "Caribbean", "key": ("C", "major"), "drums": "reggae",
+         "fill": "reggae", "bpm": 110,
+         "prog": ("I", "IV", "V", "IV"),
+         "lead": ("steel_drum_synth", "none", 0.25, 0.3),
+         "pad": ("acoustic_guitar_synth", "none", -0.3),
+         "bass_lp": 500, "reverb_type": "plate"},
+        {"name": "Accordion Waltz", "key": ("D", "minor"), "drums": "waltz",
+         "fill": "jazz", "bpm": 88,
+         "prog": ("i", "iv", "V", "i"),
+         "lead": ("accordion_synth", "organ", 0.2, 0.1),
+         "pad": ("strings_synth", "pad", -0.2),
+         "bass_lp": 500, "reverb_type": "plate"},
+        {"name": "Kalimba Dreams", "key": ("G", "major"), "drums": "cajon folk",
+         "fill": "bossa nova", "bpm": 95,
+         "prog": ("I", "vi", "IV", "V"),
+         "lead": ("kalimba_synth", "none", 0.35, 0.2),
+         "pad": ("piano_synth", "none", -0.2),
+         "bass_lp": 400, "reverb_type": "taj_mahal"},
+        {"name": "Outback Drone", "key": ("E", "minor"), "drums": "djembe",
+         "fill": "afrobeat", "bpm": 70,
+         "prog": ("i", "iv", "i", "V"),
+         "lead": ("didgeridoo_synth", "pad", 0.3, 0.0),
+         "pad": ("granular_synth", "pad", 0.0),
+         "bass_lp": 200, "reverb_type": "cave"},
+        {"name": "Highland", "key": ("A", "minor"), "drums": "flamenco",
+         "fill": "rock", "bpm": 95,
+         "prog": ("i", "iv", "V", "i"),
+         "lead": ("bagpipe_synth", "organ", 0.15, 0.0),
+         "pad": ("strings_synth", "pad", -0.2),
+         "bass_lp": 400, "reverb_type": "cathedral"},
+        {"name": "Nashville Tears", "key": ("G", "major"), "drums": "country",
+         "fill": "rock", "bpm": 85,
+         "prog": ("I", "IV", "V", "IV"),
+         "lead": ("pedal_steel_synth", "strings", 0.35, 0.2),
+         "pad": ("piano_synth", "none", -0.3),
+         "bass_lp": 500, "reverb_type": "spring"},
+        {"name": "Tabla Fusion", "key": ("E", "minor"), "drums": "teental",
+         "fill": "rock", "bpm": 120,
+         "prog": ("i", "iv", "V", "i"),
+         "lead": ("sitar_synth", "none", 0.3, 0.2),
+         "pad": ("vocal_synth", "pad", 0.0),
+         "bass_lp": 400, "reverb_type": "taj_mahal"},
     ]
 
     mood = random.choice(moods)
@@ -375,7 +423,10 @@ def cmd_demo(args):
     print(f"     {mood['drums']} | {lead_synth} lead | {pad_synth} pad | {mood['reverb_type']} reverb")
     print()
 
-    play_score(score)
+    try:
+        play_score(score)
+    except KeyboardInterrupt:
+        pass
     print("  ♫")
 
 

pytheory/play.py

@@ -909,6 +909,149 @@ def saxophone_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
     return (peak * wave).astype(numpy.int16)
 
 
+def vocal_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE, lyric="ah"):
+    """Vocal/formant synthesis — sings vowel sounds at a given pitch.
+
+    Models the human voice with:
+    1. LF glottal model — asymmetric pulse with sharp closure (not just sines)
+    2. 5 parallel resonant formant filters (real voice has 5 formant peaks)
+    3. Jitter + shimmer (natural pitch/amplitude irregularity)
+    4. Aspiration noise mixed with the glottal source
+    5. Consonant onsets (plosives, sibilants, nasals, etc.)
+    """
+    import scipy.signal as _sig
+
+    # 5-formant table: (F1, F2, F3, F4, F5) frequencies and bandwidths
+    # Based on Peterson & Barney (1952) measurements, male voice
+    FORMANTS = {
+        'a': [(800, 130), (1200, 100), (2500, 140), (3300, 250), (3750, 300)],
+        'e': [(530, 80),  (1850, 100), (2500, 130), (3300, 250), (3750, 300)],
+        'i': [(280, 60),  (2250, 100), (2900, 120), (3350, 250), (3750, 300)],
+        'o': [(500, 100), (1000, 80),  (2500, 140), (3300, 250), (3750, 300)],
+        'u': ((325, 70),  (700, 60),   (2530, 140), (3300, 250), (3750, 300)),
+    }
+    # Formant gains (relative amplitude per formant)
+    FGAINS = [1.0, 0.8, 0.5, 0.25, 0.15]
+
+    rng = numpy.random.default_rng(int(hz * 100 + len(lyric) * 7) % 2**31)
+    t = numpy.arange(n_samples, dtype=numpy.float64) / SAMPLE_RATE
+
+    # Parse vowels from lyric
+    vowels_in_lyric = [c.lower() for c in lyric if c.lower() in FORMANTS]
+    if not vowels_in_lyric:
+        vowels_in_lyric = ['a']
+
+    # ── Glottal source: LF model approximation ──
+    # Asymmetric pulse: slow open phase, sharp closure, then closed phase.
+    # Much more "voice-like" than a sine or sawtooth.
+    # Jitter (pitch irregularity) + shimmer (amplitude irregularity)
+    jitter = rng.normal(0, hz * 0.001, n_samples)  # ~0.1% pitch jitter
+    shimmer = 1.0 + rng.normal(0, 0.008, n_samples)  # ~0.8% amp shimmer
+    # Vibrato
+    vib = hz * 0.001 * numpy.sin(2 * numpy.pi * 5.5 * t)
+    inst_freq = hz + vib + jitter
+    phase = numpy.cumsum(2 * numpy.pi * inst_freq / SAMPLE_RATE)
+    # LF glottal shape: sharper falling edge via phase shaping
+    saw = (phase / (2 * numpy.pi)) % 1.0  # 0 to 1 sawtooth
+    # Asymmetric: slow rise (60%), fast fall (40%)
+    glottal = numpy.where(saw < 0.6,
+                          numpy.sin(numpy.pi * saw / 0.6),   # smooth rise
+                          -numpy.sin(numpy.pi * (saw - 0.6) / 0.4) * 0.8)  # sharp fall
+    glottal *= shimmer
+
+    # Aspiration noise (breathiness) — subtle
+    breath = rng.normal(0, 0.04, n_samples)
+    source = glottal * 0.92 + breath * 0.08
+
+    # ── Formant filtering ──
+    n_vowels = len(vowels_in_lyric)
+    out = numpy.zeros(n_samples, dtype=numpy.float64)
+
+    if n_vowels == 1:
+        # Single vowel — filter the whole thing
+        formants = FORMANTS[vowels_in_lyric[0]]
+        for (fc, bw), gain in zip(formants, FGAINS):
+            lo = max(20, fc - bw)
+            hi = min(SAMPLE_RATE // 2 - 1, fc + bw)
+            if lo < hi:
+                bp, ap = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
+                out += _sig.lfilter(bp, ap, source).astype(numpy.float64) * gain
+    else:
+        # Multiple vowels — crossfade formants
+        samples_per_vowel = n_samples // n_vowels
+        for vi, vowel in enumerate(vowels_in_lyric):
+            formants = FORMANTS[vowel]
+            start = vi * samples_per_vowel
+            end = n_samples if vi == n_vowels - 1 else start + samples_per_vowel
+            seg = source[start:end].copy()
+            seg_out = numpy.zeros_like(seg)
+            for (fc, bw), gain in zip(formants, FGAINS):
+                lo = max(20, fc - bw)
+                hi = min(SAMPLE_RATE // 2 - 1, fc + bw)
+                if lo < hi:
+                    bp, ap = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
+                    seg_out += _sig.lfilter(bp, ap, seg).astype(numpy.float64) * gain
+            # Crossfade
+            fade = min(int(SAMPLE_RATE * 0.02), len(seg_out) // 4)
+            if vi > 0 and fade > 0:
+                seg_out[:fade] *= numpy.linspace(0, 1, fade)
+            if vi < n_vowels - 1 and fade > 0:
+                seg_out[-fade:] *= numpy.linspace(1, 0, fade)
+            out[start:end] += seg_out[:end - start]
+
+    # ── Consonant onsets ──
+    lyric_lower = lyric.lower()
+    if lyric_lower and lyric_lower[0] not in 'aeiou':
+        c = lyric_lower[0]
+        cl = min(int(SAMPLE_RATE * 0.035), n_samples)
+        if c in 'tdkpb':
+            burst = rng.uniform(-0.5, 0.5, cl) * numpy.exp(-numpy.linspace(0, 18, cl))
+            out[:cl] = burst + out[:cl] * 0.2
+        elif c in 'sz':
+            sib = rng.uniform(-0.4, 0.4, cl)
+            if cl > 20:
+                bl, al = _sig.butter(2, [3000, min(8000, SAMPLE_RATE//2-1)], btype='band', fs=SAMPLE_RATE)
+                sib = _sig.lfilter(bl, al, numpy.pad(sib, (0, max(0, n_samples-cl))))[:cl]
+            sib *= numpy.exp(-numpy.linspace(0, 10, cl))
+            out[:cl] = sib * 0.6 + out[:cl] * 0.4
+        elif c in 'mn':
+            nl = min(int(SAMPLE_RATE * 0.06), n_samples)
+            nasal = numpy.sin(2*numpy.pi*250*t[:nl]) * 0.4 * numpy.exp(-numpy.linspace(0, 4, nl))
+            out[:nl] = nasal + out[:nl] * 0.4
+        elif c in 'fv':
+            fric = rng.uniform(-0.25, 0.25, cl) * numpy.exp(-numpy.linspace(0, 12, cl))
+            out[:cl] = fric * 0.5 + out[:cl] * 0.5
+        elif c in 'lr':
+            gl = min(int(SAMPLE_RATE * 0.05), n_samples)
+            ghz = hz * 0.7 + hz * 0.3 * numpy.linspace(0, 1, gl)
+            glide = numpy.sin(numpy.cumsum(2*numpy.pi*ghz/SAMPLE_RATE)) * 0.35
+            out[:gl] = glide + out[:gl] * 0.65
+        elif c == 'h':
+            hl = min(int(SAMPLE_RATE * 0.05), n_samples)
+            asp = rng.uniform(-0.4, 0.4, hl) * numpy.exp(-numpy.linspace(0, 5, hl))
+            out[:hl] = asp * 0.6 + out[:hl] * 0.4
+        elif c == 'w':
+            wl = min(int(SAMPLE_RATE * 0.06), n_samples)
+            ws = numpy.sin(numpy.cumsum(2*numpy.pi*hz/SAMPLE_RATE*numpy.ones(wl)))
+            if wl > 20:
+                bp, ap = _sig.butter(2, [max(20,300), min(800, SAMPLE_RATE//2-1)], btype='band', fs=SAMPLE_RATE)
+                ws = _sig.lfilter(bp, ap, ws)
+            ws *= numpy.linspace(0.5, 0, wl)
+            out[:wl] = ws * 0.4 + out[:wl] * 0.6
+
+    # Soft edges — prevent clicks at note boundaries
+    fade_samples = min(int(SAMPLE_RATE * 0.01), n_samples // 4)
+    if fade_samples > 0:
+        out[:fade_samples] *= numpy.linspace(0, 1, fade_samples)
+        out[-fade_samples:] *= numpy.linspace(1, 0, fade_samples)
+
+    mx = numpy.abs(out).max()
+    if mx > 0:
+        out /= mx
+
+    return (peak * out).astype(numpy.int16)
+
+
 def granular_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE,
                   grain_size=0.04, density=50, scatter=0.5,
                   pitch_var=12, source="saw"):
@@ -987,6 +1130,400 @@ def granular_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE,
     return (peak * out).astype(numpy.int16)
 
 
+def pedal_steel_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
+    """Pedal steel guitar — the Nashville crying sound.
+
+    Sustained steel string with natural portamento character,
+    very smooth, lots of harmonics, and a singing quality from
+    the bar sliding on the strings.
+    """
+    t = numpy.arange(n_samples, dtype=numpy.float64) / SAMPLE_RATE
+    rng = numpy.random.default_rng(int(hz * 100) % 2**31)
+    # Slow, singing vibrato — the bar wobbling on the strings
+    vib = hz * 0.002 * numpy.sin(2 * numpy.pi * 4.0 * t)
+    # Rich harmonics — steel bar gives a clear, singing tone
+    wave = numpy.zeros(n_samples, dtype=numpy.float64)
+    for n in range(1, 12):
+        f_n = hz * n
+        if f_n >= SAMPLE_RATE / 2:
+            break
+        amp = 1.0 / n * numpy.exp(-0.08 * n)
+        phase = rng.uniform(0, 2 * numpy.pi)
+        wave += amp * numpy.sin(2 * numpy.pi * (f_n + vib * n) * t + phase)
+    # Long sustain envelope
+    wave *= numpy.exp(-0.8 * t)
+    mx = numpy.abs(wave).max()
+    if mx > 0:
+        wave /= mx
+    return (peak * wave).astype(numpy.int16)
+
+
+def theremin_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
+    """Theremin — pure sine with natural wobble.
+
+    The theremin's sound is a nearly pure sine wave with slight
+    pitch instability from hand position. The eerie, sci-fi sound
+    comes from this purity combined with continuous pitch.
+    """
+    t = numpy.arange(n_samples, dtype=numpy.float64) / SAMPLE_RATE
+    # Natural hand wobble — slightly irregular vibrato
+    rng = numpy.random.default_rng(int(hz * 100) % 2**31)
+    wobble = hz * 0.004 * numpy.sin(2 * numpy.pi * 5.8 * t)
+    wobble += hz * 0.001 * rng.normal(0, 1, n_samples)
+    wave = numpy.sin(2 * numpy.pi * (hz + wobble) * t)
+    # Slight 2nd harmonic — real theremins aren't perfectly pure
+    wave += 0.08 * numpy.sin(2 * numpy.pi * (hz * 2 + wobble * 2) * t)
+    mx = numpy.abs(wave).max()
+    if mx > 0:
+        wave /= mx
+    return (peak * wave).astype(numpy.int16)
+
+
+def kalimba_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
+    """Kalimba/thumb piano — metal tines on a wooden body.
+
+    Bright, bell-like attack with inharmonic overtones from the
+    metal tines. The wooden resonator gives warmth underneath.
+    """
+    t = numpy.arange(n_samples, dtype=numpy.float64) / SAMPLE_RATE
+    # Metal tine modes — slightly inharmonic like marimba
+    wave = numpy.sin(2 * numpy.pi * hz * t) * 0.8
+    wave += numpy.sin(2 * numpy.pi * hz * 2.92 * t) * 0.25 * numpy.exp(-12 * t)
+    wave += numpy.sin(2 * numpy.pi * hz * 5.4 * t) * 0.1 * numpy.exp(-20 * t)
+    # Two-stage decay: bright attack dies fast, fundamental rings
+    decay = numpy.where(t < 0.1,
+                        numpy.exp(-3 * t),
+                        numpy.exp(-3 * 0.1) * numpy.exp(-1.5 * (t - 0.1)))
+    wave *= decay
+    # Wooden body resonance
+    import scipy.signal as _sig
+    for center, bw, gain in [(300, 100, 0.2), (600, 120, 0.15)]:
+        lo, hi = max(20, center - bw), min(SAMPLE_RATE // 2 - 1, center + bw)
+        if lo < hi:
+            bp, ap = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
+            wave += _sig.lfilter(bp, ap, wave) * gain
+    mx = numpy.abs(wave).max()
+    if mx > 0:
+        wave /= mx
+    return (peak * wave).astype(numpy.int16)
+
+
+def steel_drum_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
+    """Steel drum/pan — hammered metal with bright, ringing tone.
+
+    The steel pan has specific inharmonic partials from the
+    hand-hammered notes. Bright, tropical, bell-like.
+    """
+    t = numpy.arange(n_samples, dtype=numpy.float64) / SAMPLE_RATE
+    # Steel pan modes — distinctly metallic
+    wave = numpy.sin(2 * numpy.pi * hz * t) * 0.7
+    wave += numpy.sin(2 * numpy.pi * hz * 2.0 * t) * 0.4 * numpy.exp(-5 * t)
+    wave += numpy.sin(2 * numpy.pi * hz * 3.01 * t) * 0.25 * numpy.exp(-8 * t)
+    wave += numpy.sin(2 * numpy.pi * hz * 4.1 * t) * 0.15 * numpy.exp(-12 * t)
+    wave += numpy.sin(2 * numpy.pi * hz * 5.3 * t) * 0.08 * numpy.exp(-18 * t)
+    # Mallet impact
+    rng = numpy.random.default_rng(int(hz * 100) % 2**31)
+    hit_len = min(int(SAMPLE_RATE * 0.008), n_samples)
+    hit = rng.uniform(-0.2, 0.2, hit_len) * numpy.exp(-numpy.linspace(0, 12, hit_len))
+    wave[:hit_len] += hit
+    # Two-stage decay
+    decay = numpy.where(t < 0.15,
+                        numpy.exp(-4 * t),
+                        numpy.exp(-4 * 0.15) * numpy.exp(-1.2 * (t - 0.15)))
+    wave *= decay
+    mx = numpy.abs(wave).max()
+    if mx > 0:
+        wave /= mx
+    return (peak * wave).astype(numpy.int16)
+
+
+def harmonium_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
+    """Harmonium — Indian pump organ, single free reed per note.
+
+    Unlike accordion (doubled musette reeds), the harmonium has one
+    reed per note — no beating, just a pure, nasal, reedy tone.
+    Constant bellows pressure, warm but slightly buzzy. The sound
+    of kirtan, qawwali, and devotional music.
+    """
+    t = numpy.arange(n_samples, dtype=numpy.float64) / SAMPLE_RATE
+    rng = numpy.random.default_rng(int(hz * 100) % 2**31)
+
+    # Single reed — odd harmonics stronger (like clarinet but warmer)
+    wave = numpy.zeros(n_samples, dtype=numpy.float64)
+    for n in range(1, 12):
+        f_n = hz * n
+        if f_n >= SAMPLE_RATE / 2:
+            break
+        amp = (1.0 / n) * (1.0 if n % 2 == 1 else 0.5)
+        phase = rng.uniform(0, 2 * numpy.pi)
+        wave += amp * numpy.sin(2 * numpy.pi * f_n * t + phase)
+
+    # Bellows pressure — gentle swell, slower than accordion
+    bellows = 0.9 + 0.1 * numpy.sin(2 * numpy.pi * 0.5 * t)
+    wave *= bellows
+
+    # Nasal character — slight midrange boost
+    import scipy.signal as _sig
+    center = min(1200, hz * 3)
+    lo = max(20, int(center - 300))
+    hi = min(SAMPLE_RATE // 2 - 1, int(center + 300))
+    if lo < hi:
+        bp, ap = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
+        nasal = _sig.lfilter(bp, ap, wave) * 0.2
+        wave += nasal
+
+    mx = numpy.abs(wave).max()
+    if mx > 0:
+        wave /= mx
+    return (peak * wave).astype(numpy.int16)
+
+
+def accordion_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
+    """Accordion — bellows-driven free reeds.
+
+    Two reeds per note slightly detuned (musette tuning) create
+    the characteristic beating/tremolo. Rich in harmonics from
+    the reed vibration.
+    """
+    t = numpy.arange(n_samples, dtype=numpy.float64) / SAMPLE_RATE
+    rng = numpy.random.default_rng(int(hz * 100) % 2**31)
+    # Two reeds slightly detuned — musette beating
+    detune_cents = 8
+    hz2 = hz * (2 ** (detune_cents / 1200))
+    # Reed harmonics — rich, like a square-ish wave but warmer
+    wave = numpy.zeros(n_samples, dtype=numpy.float64)
+    for reed_hz in [hz, hz2]:
+        for n in range(1, 10):
+            f_n = reed_hz * n
+            if f_n >= SAMPLE_RATE / 2:
+                break
+            # Odd harmonics stronger (reed character)
+            amp = (1.0 / n) * (1.2 if n % 2 == 1 else 0.6)
+            phase = rng.uniform(0, 2 * numpy.pi)
+            wave += amp * numpy.sin(2 * numpy.pi * f_n * t + phase)
+    wave *= 0.5  # normalize for two reeds
+    # Bellows pressure variation — slow amplitude swell
+    bellows = 0.85 + 0.15 * numpy.sin(2 * numpy.pi * 0.8 * t)
+    wave *= bellows
+    mx = numpy.abs(wave).max()
+    if mx > 0:
+        wave /= mx
+    return (peak * wave).astype(numpy.int16)
+
+
+def didgeridoo_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
+    """Didgeridoo — circular breathing drone through a wooden tube.
+
+    Deep fundamental with strong odd harmonics from the cylindrical
+    bore. The overtone singing technique creates shifting formants.
+    Buzzy, droning, primal.
+    """
+    t = numpy.arange(n_samples, dtype=numpy.float64) / SAMPLE_RATE
+    rng = numpy.random.default_rng(int(hz * 100) % 2**31)
+    # Lip buzz source — rich, raw
+    phase = numpy.cumsum(2 * numpy.pi * hz / SAMPLE_RATE * numpy.ones(n_samples))
+    buzz = numpy.zeros(n_samples, dtype=numpy.float64)
+    for n in range(1, 15):
+        if hz * n >= SAMPLE_RATE / 2:
+            break
+        # Odd harmonics stronger (cylindrical bore, like clarinet)
+        amp = (1.0 / n) * (1.0 if n % 2 == 1 else 0.4)
+        buzz += amp * numpy.sin(phase * n + rng.uniform(0, 2 * numpy.pi))
+    # Shifting formant — the overtone singing effect
+    # Sweeps slowly between 500Hz and 1500Hz
+    formant_center = 800 + 400 * numpy.sin(2 * numpy.pi * 0.3 * t)
+    import scipy.signal as _sig
+    # Block-process the formant sweep
+    block = 2048
+    out = numpy.zeros(n_samples, dtype=numpy.float64)
+    for i in range(0, n_samples, block):
+        end = min(i + block, n_samples)
+        fc = formant_center[(i + end) // 2]
+        lo = max(20, int(fc - 300))
+        hi = min(SAMPLE_RATE // 2 - 1, int(fc + 300))
+        if lo < hi:
+            bp, ap = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
+            seg = _sig.lfilter(bp, ap, buzz[i:end])
+            out[i:end] = buzz[i:end] * 0.5 + seg * 0.5
+        else:
+            out[i:end] = buzz[i:end]
+    # Breath noise
+    breath = rng.normal(0, 0.04, n_samples)
+    out += breath
+    mx = numpy.abs(out).max()
+    if mx > 0:
+        out /= mx
+    return (peak * out).astype(numpy.int16)
+
+
+def bagpipe_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
+    """Bagpipes — chanter reed with constant drone pressure.
+
+    The chanter (melody pipe) uses a double reed like an oboe
+    but with more buzz and brightness. The constant air pressure
+    from the bag means no dynamics — always ff.
+    """
+    t = numpy.arange(n_samples, dtype=numpy.float64) / SAMPLE_RATE
+    rng = numpy.random.default_rng(int(hz * 100) % 2**31)
+    # Chanter — all harmonics, bright and reedy
+    wave = numpy.zeros(n_samples, dtype=numpy.float64)
+    for n in range(1, 18):
+        f_n = hz * n
+        if f_n >= SAMPLE_RATE / 2:
+            break
+        # Peaked around harmonics 3-7 (the piercing brightness)
+        amp = (1.0 / n) * numpy.exp(-0.03 * (n - 5) ** 2)
+        phase = rng.uniform(0, 2 * numpy.pi)
+        wave += amp * numpy.sin(2 * numpy.pi * f_n * t + phase)
+    # Reed buzz — more than oboe
+    reed = rng.normal(0, 0.08, n_samples)
+    import scipy.signal as _sig
+    lo = max(20, int(hz * 2))
+    hi = min(SAMPLE_RATE // 2 - 1, int(hz * 8))
+    if lo < hi:
+        br, ar = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
+        reed = _sig.lfilter(br, ar, reed).astype(numpy.float64) * 1.5
+    wave += reed
+    # Bag pressure wobble — very subtle
+    bag = 1.0 + 0.02 * numpy.sin(2 * numpy.pi * 1.5 * t)
+    wave *= bag
+    mx = numpy.abs(wave).max()
+    if mx > 0:
+        wave /= mx
+    return (peak * wave).astype(numpy.int16)
+
+
+def banjo_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
+    """Banjo — steel strings on a drum-head body.
+
+    The banjo's distinctive twang comes from the membrane head
+    (like a drum skin) instead of a wooden soundboard. This gives
+    a sharp attack, bright tone, and fast decay with a nasal,
+    metallic quality. The 5th string drone adds shimmer.
+    """
+    period = int(SAMPLE_RATE / hz)
+    if period < 2:
+        period = 2
+    rng = numpy.random.default_rng(int(hz * 100) % 2**31)
+
+    # Steel string — bright, sharp attack
+    buf = rng.uniform(-0.9, 0.9, period).astype(numpy.float64)
+    # Minimal filtering — banjo keeps the brightness
+    for k in range(period - 1):
+        buf[k] = 0.7 * buf[k] + 0.3 * buf[k + 1]
+
+    out = numpy.zeros(n_samples, dtype=numpy.float64)
+    for i in range(n_samples):
+        out[i] = buf[i % period]
+        next_idx = (i + 1) % period
+        # Moderate decay — drum head rings but shorter than guitar
+        buf[i % period] = 0.5 * (buf[i % period] + buf[next_idx]) * 0.9988
+
+    # Drum-head resonance — nasal, ringy, mid-frequency peaks
+    # The membrane head rings more than wood — that's the twang
+    import scipy.signal as _sig
+    for center, bw, gain in [(600, 200, 0.5), (1500, 300, 0.4), (3000, 500, 0.25)]:
+        lo = max(20, center - bw)
+        hi = min(SAMPLE_RATE // 2 - 1, center + bw)
+        if lo < hi:
+            bp, ap = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
+            out += _sig.lfilter(bp, ap, out) * gain
+
+    mx = numpy.abs(out).max()
+    if mx > 0:
+        out /= mx
+    return (peak * out).astype(numpy.int16)
+
+
+def mandolin_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
+    """Mandolin — paired steel strings, bright and ringing.
+
+    The mandolin has 4 courses of paired strings, tuned in unison.
+    The doubled strings create natural chorus. Bright attack from
+    the plectrum, small body with high-frequency resonance.
+    """
+    period = int(SAMPLE_RATE / hz)
+    if period < 2:
+        period = 2
+    rng = numpy.random.default_rng(int(hz * 100) % 2**31)
+
+    # Two strings per course — slightly detuned for natural chorus
+    buf1 = rng.uniform(-0.8, 0.8, period).astype(numpy.float64)
+    period2 = max(2, period + rng.integers(-1, 2))
+    buf2 = rng.uniform(-0.8, 0.8, period2).astype(numpy.float64)
+    # Light filtering — steel is brighter than nylon
+    for k in range(period - 1):
+        buf1[k] = 0.65 * buf1[k] + 0.35 * buf1[k + 1]
+    for k in range(period2 - 1):
+        buf2[k] = 0.65 * buf2[k] + 0.35 * buf2[k + 1]
+
+    out = numpy.zeros(n_samples, dtype=numpy.float64)
+    for i in range(n_samples):
+        s1 = buf1[i % period]
+        s2 = buf2[i % period2]
+        out[i] = s1 * 0.55 + s2 * 0.45
+        next1 = (i + 1) % period
+        buf1[i % period] = 0.5 * (s1 + buf1[next1]) * 0.9988
+        next2 = (i + 1) % period2
+        buf2[i % period2] = 0.5 * (s2 + buf2[next2]) * 0.9988
+
+    # Small bright body — higher resonance than guitar
+    import scipy.signal as _sig
+    for center, bw, gain in [(500, 120, 0.3), (1000, 200, 0.25), (2000, 300, 0.15)]:
+        lo = max(20, center - bw)
+        hi = min(SAMPLE_RATE // 2 - 1, center + bw)
+        if lo < hi:
+            bp, ap = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
+            out += _sig.lfilter(bp, ap, out) * gain
+
+    mx = numpy.abs(out).max()
+    if mx > 0:
+        out /= mx
+    return (peak * out).astype(numpy.int16)
+
+
+def ukulele_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
+    """Ukulele — nylon strings on a small resonant body.
+
+    Brighter and thinner than guitar, shorter sustain. The small
+    body gives a mid-heavy resonance (no deep bass). Nylon strings
+    have a softer, warmer attack than steel.
+    """
+    period = int(SAMPLE_RATE / hz)
+    if period < 2:
+        period = 2
+    rng = numpy.random.default_rng(int(hz * 100) % 2**31)
+
+    # Nylon string — soft noise
+    buf = rng.uniform(-0.5, 0.5, period).astype(numpy.float64)
+    for _ in range(5):
+        for k in range(period - 1):
+            buf[k] = 0.55 * buf[k] + 0.45 * buf[k + 1]
+
+    out = numpy.zeros(n_samples, dtype=numpy.float64)
+    for i in range(n_samples):
+        out[i] = buf[i % period]
+        next_idx = (i + 1) % period
+        buf[i % period] = 0.5 * (buf[i % period] + buf[next_idx]) * 0.998
+
+    # Small body resonance — mid-heavy, no deep bass
+    import scipy.signal as _sig
+    for center, bw, gain in [(350, 100, 0.35), (700, 150, 0.25), (1200, 200, 0.15)]:
+        lo = max(20, center - bw)
+        hi = min(SAMPLE_RATE // 2 - 1, center + bw)
+        if lo < hi:
+            bp, ap = _sig.butter(2, [lo, hi], btype='band', fs=SAMPLE_RATE)
+            out += _sig.lfilter(bp, ap, out) * gain
+
+    bl, al = _sig.butter(2, min(6000, hz * 12), btype='low', fs=SAMPLE_RATE)
+    out = _sig.lfilter(bl, al, out)
+
+    mx = numpy.abs(out).max()
+    if mx > 0:
+        out /= mx
+    return (peak * out).astype(numpy.int16)
+
+
 def acoustic_guitar_wave(hz, peak=SAMPLE_PEAK, n_samples=SAMPLE_RATE):
     """Acoustic guitar — Karplus-Strong with wooden body resonance.
 
@@ -1245,8 +1782,11 @@ def _play_for(sample_wave, ms):
     """Play the given NumPy sample array through the speakers."""
     normalized_wave = sample_wave.astype(numpy.float32) / SAMPLE_PEAK
     _sd = _get_sd()
-    _sd.play(normalized_wave, SAMPLE_RATE)
-    _sd.wait()
+    try:
+        _sd.play(normalized_wave, SAMPLE_RATE)
+        _sd.wait()
+    except KeyboardInterrupt:
+        _sd.stop()
 
 
 class Synth(Enum):
@@ -1290,6 +1830,18 @@ class Synth(Enum):
     TIMPANI = "timpani_synth"
     SAXOPHONE = "saxophone_synth"
     GRANULAR = "granular_synth"
+    VOCAL = "vocal_synth"
+    PEDAL_STEEL = "pedal_steel_synth"
+    THEREMIN = "theremin_synth"
+    KALIMBA = "kalimba_synth"
+    STEEL_DRUM = "steel_drum_synth"
+    HARMONIUM = "harmonium_synth"
+    ACCORDION = "accordion_synth"
+    DIDGERIDOO = "didgeridoo_synth"
+    BAGPIPE = "bagpipe_synth"
+    BANJO = "banjo_synth"
+    MANDOLIN = "mandolin_synth"
+    UKULELE = "ukulele_synth"
     ACOUSTIC_GUITAR = "acoustic_guitar_synth"
     SITAR = "sitar_synth"
     ELECTRIC_GUITAR = "electric_guitar_synth"
@@ -1312,7 +1864,13 @@ _SYNTH_FUNCTIONS = {
     "harpsichord_synth": harpsichord_wave, "cello_synth": cello_wave,
     "harp_synth": harp_wave, "upright_bass_synth": upright_bass_wave,
     "timpani_synth": timpani_wave, "saxophone_synth": saxophone_wave,
-    "granular_synth": granular_wave,
+    "granular_synth": granular_wave, "vocal_synth": vocal_wave,
+    "pedal_steel_synth": pedal_steel_wave, "theremin_synth": theremin_wave,
+    "kalimba_synth": kalimba_wave, "steel_drum_synth": steel_drum_wave,
+    "harmonium_synth": harmonium_wave, "accordion_synth": accordion_wave, "didgeridoo_synth": didgeridoo_wave,
+    "bagpipe_synth": bagpipe_wave,
+    "banjo_synth": banjo_wave, "mandolin_synth": mandolin_wave,
+    "ukulele_synth": ukulele_wave,
     "acoustic_guitar_synth": acoustic_guitar_wave,
     "sitar_synth": sitar_wave, "electric_guitar_synth": electric_guitar_wave,
 }
@@ -2068,6 +2626,114 @@ def _synth_mridangam_tha(n_samples):
     return out
 
 
+def _synth_doumbek_dum(n_samples):
+    """Doumbek Dum — open center strike, deep and round."""
+    t = numpy.arange(n_samples, dtype=numpy.float32) / SAMPLE_RATE
+    freq = 80 + 40 * numpy.exp(-25 * t)
+    phase = 2 * numpy.pi * numpy.cumsum(freq) / SAMPLE_RATE
+    body = numpy.sin(phase) * _exp_decay(n_samples, 8) * 0.8
+    thump_len = min(int(SAMPLE_RATE * 0.04), n_samples)
+    import scipy.signal as _sig
+    thump = _noise(thump_len)
+    if thump_len > 20:
+        bl, al = _sig.butter(2, [50, 250], btype='band', fs=SAMPLE_RATE)
+        thump = _sig.lfilter(bl, al, numpy.pad(thump, (0, max(0, n_samples - thump_len))))[:thump_len].astype(numpy.float32)
+    thump *= _exp_decay(thump_len, 22) * 0.7
+    body[:thump_len] += thump
+    return numpy.tanh(body * 1.3).astype(numpy.float32)
+
+
+def _synth_doumbek_tek(n_samples):
+    """Doumbek Tek — sharp edge strike, bright and cutting."""
+    t = numpy.arange(n_samples, dtype=numpy.float32) / SAMPLE_RATE
+    ring = numpy.sin(2 * numpy.pi * 400 * t) * _exp_decay(n_samples, 22) * 0.5
+    ring2 = numpy.sin(2 * numpy.pi * 900 * t) * 0.3 * _exp_decay(n_samples, 30)
+    click_len = min(int(SAMPLE_RATE * 0.005), n_samples)
+    click = _noise(click_len) * _exp_decay(click_len, 300) * 0.9
+    import scipy.signal as _sig
+    if click_len > 10:
+        bl, al = _sig.butter(2, [2000, min(8000, SAMPLE_RATE // 2 - 1)], btype='band', fs=SAMPLE_RATE)
+        click = _sig.lfilter(bl, al, numpy.pad(click, (0, max(0, n_samples - click_len))))[:click_len].astype(numpy.float32)
+    result = ring + ring2
+    result[:click_len] += click
+    return numpy.tanh(result * 1.8).astype(numpy.float32)
+
+
+def _synth_doumbek_ka(n_samples):
+    """Doumbek Ka — muted edge slap, short and dry."""
+    n = min(n_samples, int(SAMPLE_RATE * 0.04))
+    t = numpy.arange(n, dtype=numpy.float32) / SAMPLE_RATE
+    body = numpy.sin(2 * numpy.pi * 350 * t) * _exp_decay(n, 30) * 0.4
+    slap = _noise(min(80, n)) * _exp_decay(min(80, n), 200) * 0.7
+    result = body
+    result[:min(80, n)] += slap
+    out = numpy.zeros(n_samples, dtype=numpy.float32)
+    out[:n] = numpy.tanh(result * 1.5)
+    return out
+
+
+def _synth_cajon_bass(n_samples):
+    """Cajón bass — palm strike on center of the face.
+
+    Deep woody thump. The box resonates like a bass drum but with
+    a warmer, more wooden character.
+    """
+    t = numpy.arange(n_samples, dtype=numpy.float32) / SAMPLE_RATE
+    # Wooden box thump
+    thump_len = min(int(SAMPLE_RATE * 0.06), n_samples)
+    thump_raw = _noise(thump_len)
+    import scipy.signal as _sig
+    if thump_len > 20:
+        bl, al = _sig.butter(2, [40, 200], btype='band', fs=SAMPLE_RATE)
+        thump = _sig.lfilter(bl, al, numpy.pad(thump_raw, (0, max(0, n_samples - thump_len))))[:thump_len].astype(numpy.float32)
+    else:
+        thump = thump_raw
+    thump *= _exp_decay(thump_len, 18) * 0.8
+    body = numpy.sin(2 * numpy.pi * 70 * t) * _exp_decay(n_samples, 7) * 0.8
+    sub = _sine_f32(45, n_samples) * _exp_decay(n_samples, 9) * 0.4
+    click_len = min(200, n_samples)
+    click = _noise(click_len) * _exp_decay(click_len, 45) * 0.3
+    result = body + sub
+    result[:thump_len] += thump
+    result[:click_len] += click
+    return numpy.tanh(result * 1.3).astype(numpy.float32)
+
+
+def _synth_cajon_slap(n_samples):
+    """Cajón slap — fingers near the top edge, snare wires buzz.
+
+    Bright crack with a buzzy rattle from the internal snare wires.
+    The signature cajón sound — like a snare but woodier.
+    """
+    t = numpy.arange(n_samples, dtype=numpy.float32) / SAMPLE_RATE
+    # Snare wire buzz
+    wire = _noise(n_samples) * _exp_decay(n_samples, 18) * 0.6
+    import scipy.signal as _sig
+    bl, al = _sig.butter(2, [1500, 6000], btype='band', fs=SAMPLE_RATE)
+    wire = _sig.lfilter(bl, al, wire).astype(numpy.float32) * 1.2
+    # Wood body
+    body = numpy.sin(2 * numpy.pi * 200 * t) * _exp_decay(n_samples, 22) * 0.4
+    # Sharp slap
+    slap_len = min(int(SAMPLE_RATE * 0.008), n_samples)
+    slap = _noise(slap_len) * _exp_decay(slap_len, 200) * 0.8
+    result = body + wire
+    result[:slap_len] += slap
+    return numpy.tanh(result * 1.5).astype(numpy.float32)
+
+
+def _synth_cajon_tap(n_samples):
+    """Cajón tap — light fingertip on the face. Ghost note."""
+    n = min(n_samples, int(SAMPLE_RATE * 0.04))
+    t = numpy.arange(n, dtype=numpy.float32) / SAMPLE_RATE
+    tap = numpy.sin(2 * numpy.pi * 300 * t) * _exp_decay(n, 35) * 0.3
+    pop = _noise(min(50, n)) * _exp_decay(min(50, n), 250) * 0.5
+    result = tap
+    result[:min(50, n)] += pop
+    out = numpy.zeros(n_samples, dtype=numpy.float32)
+    out[:n] = numpy.tanh(result * 1.5)
+    return out
+
+
 def _synth_metal_kick(n_samples):
     """Metal kick — punchy with beater click. Double-bass ready.
 
@@ -2336,6 +3002,14 @@ def _render_drum_hit(sound_value, n_samples):
         DrumSound.DJEMBE_BASS.value: lambda n: _synth_djembe_bass(n),
         DrumSound.DJEMBE_TONE.value: lambda n: _synth_djembe_tone(n),
         DrumSound.DJEMBE_SLAP.value: lambda n: _synth_djembe_slap(n),
+        # Doumbek
+        DrumSound.DOUMBEK_DUM.value: lambda n: _synth_doumbek_dum(n),
+        DrumSound.DOUMBEK_TEK.value: lambda n: _synth_doumbek_tek(n),
+        DrumSound.DOUMBEK_KA.value: lambda n: _synth_doumbek_ka(n),
+        # Cajon
+        DrumSound.CAJON_BASS.value: lambda n: _synth_cajon_bass(n),
+        DrumSound.CAJON_SLAP.value: lambda n: _synth_cajon_slap(n),
+        DrumSound.CAJON_TAP.value: lambda n: _synth_cajon_tap(n),
         # Metal kit
         DrumSound.METAL_KICK.value: lambda n: _synth_metal_kick(n),
         DrumSound.METAL_SNARE.value: lambda n: _synth_metal_snare(n),
@@ -3528,8 +4202,13 @@ def _render_notes_to_buf(notes, buf, samples_per_beat, total_samples,
                         bent = src_f[idx] * (1 - frac) + src_f[numpy.minimum(idx + 1, src_len - 1)] * frac
                         waves.append((bent * SAMPLE_PEAK).astype(numpy.int16))
                 else:
-                    # Render oscillators (pass synth_kwargs for FM etc.)
-                    waves = [synth_fn(hz, n_samples=n_samples, **_skw)
+                    # Per-note kwargs (e.g. lyric for vocal synth)
+                    note_skw = dict(_skw)
+                    note_lyric = getattr(note, 'lyric', '')
+                    if note_lyric:
+                        note_skw['lyric'] = note_lyric
+                    # Render oscillators
+                    waves = [synth_fn(hz, n_samples=n_samples, **note_skw)
                              for hz in pitches]
                 # Sub-oscillator: octave-below sine
                 if sub_osc > 0:
@@ -3613,7 +4292,9 @@ def _render_notes_to_buf(notes, buf, samples_per_beat, total_samples,
                     # Right channel gets up-detuned, left gets down-detuned
                     stereo_buf[start:end, 1] += up_env * gain * spread_amt
                     stereo_buf[start:end, 0] += down_env * gain * spread_amt
-        beat_pos += note.beats
+        # hold() notes don't advance the beat position
+        if not getattr(note, '_hold', False):
+            beat_pos += note.beats
 
 
 def _render_legato_to_buf(notes, buf, samples_per_beat, total_samples,
@@ -3655,7 +4336,8 @@ def _render_legato_to_buf(notes, buf, samples_per_beat, total_samples,
             events.append((start, end, hz, vel))
         else:
             events.append((start, end, 0, vel))  # rest
-        beat_pos += note.beats
+        if not getattr(note, '_hold', False):
+            beat_pos += note.beats
 
     if not events:
         return
@@ -3920,6 +4602,14 @@ def render_score(score):
         DrumSound.DJEMBE_BASS.value: 0.0,
         DrumSound.DJEMBE_TONE.value: 0.1,
         DrumSound.DJEMBE_SLAP.value: -0.1,
+        # Doumbek
+        DrumSound.DOUMBEK_DUM.value: 0.0,
+        DrumSound.DOUMBEK_TEK.value: 0.1,
+        DrumSound.DOUMBEK_KA.value: -0.1,
+        # Cajon — centered (single instrument)
+        DrumSound.CAJON_BASS.value: 0.0,
+        DrumSound.CAJON_SLAP.value: 0.0,
+        DrumSound.CAJON_TAP.value: 0.1,
         # Metal kit
         DrumSound.METAL_KICK.value: 0.0,
         DrumSound.METAL_SNARE.value: 0.0,
@@ -4046,8 +4736,11 @@ def play_score(score):
     """
     buf = render_score(score)
     _sd = _get_sd()
-    _sd.play(buf, SAMPLE_RATE)
-    _sd.wait()
+    try:
+        _sd.play(buf, SAMPLE_RATE)
+        _sd.wait()
+    except KeyboardInterrupt:
+        _sd.stop()
 
 
 # ── MIDI export ─────────────────────────────────────────────────────────────

pytheory/repl.py

@@ -77,6 +77,7 @@ def cmd_help(session, args):
   Parts:
     part lead saw pluck         score.part("lead", synth="saw", envelope="pluck")
     part bass sine              score.part("bass", synth="sine")
+    part lead instrument piano  score.part("lead", instrument="piano")
     part                        list all parts
 
   Notes (on active part):
@@ -85,6 +86,12 @@ def cmd_help(session, args):
     rest 2                      part.rest(2.0)
     arp Am updown 2 2           part.arpeggio("Am", pattern="updown", bars=2, octaves=2)
     prog I V vi IV              part adds key.progression(...)
+    strum Am 2 down             part.strum("Am", 2, direction="down")
+    strum G 2 up 0.1            lazy strum (strum_time=0.1)
+    roll C3 4                   part.roll("C3", 4) — timpani/tremolo
+    roll C3 4 30 110            roll with velocity ramp
+    bend C5 1 2                 part.add("C5", 1, bend=2) — bend up 2 semitones
+    bend C5 1 -1                bend down a half step
 
   Effects (on active part):
     reverb 0.4                  reverb=0.4
@@ -110,6 +117,12 @@ def cmd_help(session, args):
     fingering Am                guitar chord fingering
     diagram [mode] [frets]      scale diagram on guitar
 
+  Tuning:
+    temperament equal           set temperament (equal/pythagorean/meantone/just)
+    temperament                 show current temperament
+    reference 432               set reference pitch (default 440)
+    instruments                 list all available instruments
+
   Session:
     show                        score info
     status                      current state
@@ -197,12 +210,22 @@ def cmd_part(session, args):
         return
 
     name = args[0]
-    synth = args[1] if len(args) > 1 else "saw"
-    envelope = args[2] if len(args) > 2 else "pluck"
 
     if name not in session.parts:
-        session.parts[name] = session.score.part(name, synth=synth, envelope=envelope)
-        print(f"  score.part(\"{name}\", synth=\"{synth}\", envelope=\"{envelope}\")")
+        # Check if second arg is "instrument" keyword or an instrument name
+        if len(args) > 1 and args[1] == "instrument" and len(args) > 2:
+            instrument = args[2]
+            session.parts[name] = session.score.part(name, instrument=instrument)
+            print(f"  score.part(\"{name}\", instrument=\"{instrument}\")")
+        elif len(args) > 1 and args[1] in _INSTRUMENT_NAMES:
+            instrument = args[1]
+            session.parts[name] = session.score.part(name, instrument=instrument)
+            print(f"  score.part(\"{name}\", instrument=\"{instrument}\")")
+        else:
+            synth = args[1] if len(args) > 1 else "saw"
+            envelope = args[2] if len(args) > 2 else "pluck"
+            session.parts[name] = session.score.part(name, synth=synth, envelope=envelope)
+            print(f"  score.part(\"{name}\", synth=\"{synth}\", envelope=\"{envelope}\")")
     else:
         print(f"  → {name}")
     session.current_part = session.parts[name]
@@ -534,6 +557,97 @@ def cmd_identify(session, args):
         print(f"  error: {e}")
 
 
+def cmd_strum(session, args):
+    """Strum a chord on a fretboard-equipped part."""
+    if not args:
+        print("  usage: strum Am [beats] [down|up] [strum_time]")
+        return
+    part = _require_part(session)
+    chord_name = args[0]
+    beats = float(args[1]) if len(args) > 1 else 1.0
+    direction = args[2] if len(args) > 2 else "down"
+    strum_time = float(args[3]) if len(args) > 3 else 0.05
+    try:
+        part.strum(chord_name, beats, direction=direction, strum_time=strum_time)
+        print(f"  .strum(\"{chord_name}\", {beats}, direction=\"{direction}\", "
+              f"strum_time={strum_time})")
+    except Exception as e:
+        print(f"  error: {e}")
+
+
+def cmd_roll(session, args):
+    """Play a roll (rapid repeated notes with velocity ramp)."""
+    if not args:
+        print("  usage: roll C3 [beats] [vel_start] [vel_end]")
+        return
+    part = _require_part(session)
+    tone = args[0]
+    beats = float(args[1]) if len(args) > 1 else 4.0
+    vel_start = int(args[2]) if len(args) > 2 else 40
+    vel_end = int(args[3]) if len(args) > 3 else 100
+    try:
+        part.roll(tone, beats, velocity_start=vel_start, velocity_end=vel_end)
+        print(f"  .roll(\"{tone}\", {beats}, velocity_start={vel_start}, "
+              f"velocity_end={vel_end})")
+    except Exception as e:
+        print(f"  error: {e}")
+
+
+def cmd_bend(session, args):
+    """Add a note with pitch bend."""
+    if len(args) < 3:
+        print("  usage: bend C5 1 2       (note, beats, semitones)")
+        print("         bend C5 1 -1      (bend down)")
+        return
+    part = _require_part(session)
+    note = args[0]
+    beats = float(args[1])
+    bend = float(args[2])
+    bend_type = args[3] if len(args) > 3 else "smooth"
+    try:
+        part.add(note, beats, bend=bend, bend_type=bend_type)
+        print(f"  .add(\"{note}\", {beats}, bend={bend}, bend_type=\"{bend_type}\")")
+    except Exception as e:
+        print(f"  error: {e}")
+
+
+def cmd_temperament(session, args):
+    """Set or show the tuning temperament."""
+    if not args:
+        temp = getattr(session.score, 'temperament', 'equal')
+        ref = getattr(session.score, 'reference_pitch', 440.0)
+        print(f"  temperament={temp}  reference={ref} Hz")
+        print(f"  available: equal, pythagorean, meantone, just")
+        return
+    temp = args[0]
+    valid = ["equal", "pythagorean", "meantone", "just"]
+    if temp not in valid:
+        print(f"  unknown temperament: {temp}")
+        print(f"  available: {', '.join(valid)}")
+        return
+    session.score.temperament = temp
+    print(f"  temperament={temp}")
+
+
+def cmd_reference(session, args):
+    """Set the reference pitch (A4 frequency)."""
+    if not args:
+        ref = getattr(session.score, 'reference_pitch', 440.0)
+        print(f"  reference={ref} Hz")
+        return
+    ref = float(args[0])
+    session.score.reference_pitch = ref
+    print(f"  reference={ref} Hz")
+
+
+def cmd_instruments(session, args):
+    """List all available instruments."""
+    cols = 3
+    for i in range(0, len(_INSTRUMENT_NAMES), cols):
+        row = _INSTRUMENT_NAMES[i:i + cols]
+        print("  " + "  ".join(f"{name:<22s}" for name in row))
+
+
 def cmd_circle(session, args):
     """Show circle of fifths."""
     tonic = args[0] if args else session.key.tonic_name
@@ -560,7 +674,10 @@ def cmd_clear(session, args):
 def cmd_status(session, args):
     parts = ", ".join(session.parts.keys()) if session.parts else "none"
     active = session.current_part.name if session.current_part else "none"
+    temp = getattr(session.score, 'temperament', 'equal')
+    ref = getattr(session.score, 'reference_pitch', 440.0)
     print(f"  key={session.key}  bpm={session.bpm}  swing={session.swing}")
+    print(f"  temperament={temp}  reference={ref} Hz")
     print(f"  drums={session._drum_preset or 'none'}  parts=[{parts}]  active={active}")
 
 
@@ -607,6 +724,12 @@ COMMANDS = {
     "interval": cmd_interval,
     "identify": cmd_identify, "id": cmd_identify,
     "circle": cmd_circle,
+    "strum": cmd_strum,
+    "roll": cmd_roll,
+    "bend": cmd_bend,
+    "temperament": cmd_temperament, "temp": cmd_temperament,
+    "reference": cmd_reference, "ref": cmd_reference,
+    "instruments": cmd_instruments,
     "clear": cmd_clear,
     "status": cmd_status,
 }
@@ -653,9 +776,43 @@ def _prompt(session):
 # ── Tab completion ─────────────────────────────────────────────────────────
 
 _SYNTH_NAMES = ["sine", "saw", "triangle", "square", "pulse", "fm",
-                "noise", "supersaw", "pwm_slow", "pwm_fast"]
+                "noise", "supersaw", "pwm_slow", "pwm_fast",
+                "pedal_steel_synth", "theremin_synth", "kalimba_synth",
+                "steel_drum_synth", "accordion_synth", "didgeridoo_synth",
+                "bagpipe_synth", "banjo_synth", "mandolin_synth",
+                "ukulele_synth", "vocal_synth", "granular_synth",
+                "piano_synth", "organ_synth", "harpsichord_synth",
+                "strings_synth", "cello_synth", "flute_synth",
+                "clarinet_synth", "oboe_synth", "trumpet_synth",
+                "acoustic_guitar_synth", "electric_guitar_synth",
+                "bass_guitar_synth", "upright_bass_synth", "harp_synth",
+                "sitar_synth", "pluck_synth", "saxophone_synth",
+                "marimba_synth", "timpani_synth"]
+_INSTRUMENT_NAMES = [
+    # Keys
+    "piano", "electric_piano", "organ", "harpsichord", "celesta", "music_box",
+    # Strings
+    "violin", "viola", "cello", "contrabass", "string_ensemble",
+    # Woodwinds
+    "flute", "clarinet", "oboe", "bassoon",
+    # Brass
+    "trumpet", "trombone", "french_horn", "tuba", "brass_ensemble",
+    # Plucked
+    "acoustic_guitar", "electric_guitar", "clean_guitar", "crunch_guitar",
+    "distorted_guitar", "orange_crunch", "metal_guitar", "bass_guitar",
+    "upright_bass", "harp", "sitar", "pedal_steel", "theremin", "kalimba",
+    "steel_drum", "accordion", "didgeridoo", "bagpipe", "banjo", "mandolin",
+    "mandola", "ukulele", "koto",
+    # Synth presets
+    "synth_lead", "synth_pad", "synth_bass", "acid_bass",
+    "granular_pad", "vocal", "choir", "granular_texture", "808_bass",
+    # Percussion / Mallet
+    "vibraphone", "marimba", "xylophone", "glockenspiel", "tubular_bells", "timpani",
+    # Woodwinds (continued)
+    "saxophone", "alto_sax", "tenor_sax", "bari_sax",
+]
 _ENVELOPE_NAMES = ["piano", "pluck", "pad", "organ", "bell", "strings",
-                   "staccato", "none"]
+                   "staccato", "bowed", "mallet", "none"]
 _ARP_PATTERNS = ["up", "down", "updown", "downup", "random"]
 _LFO_SHAPES = ["sine", "triangle", "saw", "square"]
 _SYSTEMS = ["western", "indian", "arabic", "japanese", "blues", "gamelan"]
@@ -667,7 +824,7 @@ _CHORD_SUFFIXES = ["", "m", "7", "m7", "maj7", "dim", "aug", "sus2", "sus4",
 # Context-aware completions for the second word
 _ARG_COMPLETIONS = {
     "drums": lambda: Pattern.list_presets(),
-    "part": lambda: _SYNTH_NAMES,
+    "part": lambda: _SYNTH_NAMES + _INSTRUMENT_NAMES,
     "key": lambda: [f"{n}m" for n in _NOTE_NAMES[:12]] + _NOTE_NAMES[:12],
     "arp": lambda: [f"{n}{s}" for n in _NOTE_NAMES[:7] for s in _CHORD_SUFFIXES[:6]],
     "add": lambda: [f"{n}{o}" for n in _NOTE_NAMES[:12] for o in ["3", "4", "5"]],
@@ -679,6 +836,12 @@ _ARG_COMPLETIONS = {
                     "lowpass_q", "reverb_decay", "delay_time", "delay_feedback",
                     "distortion_drive"],
     "identify": lambda: [f"{n}{s}" for n in _NOTE_NAMES[:7] for s in _CHORD_SUFFIXES[:6]],
+    "strum": lambda: [f"{n}{s}" for n in _NOTE_NAMES[:7] for s in _CHORD_SUFFIXES[:6]],
+    "roll": lambda: [f"{n}{o}" for n in _NOTE_NAMES[:12] for o in ["2", "3", "4", "5"]],
+    "bend": lambda: [f"{n}{o}" for n in _NOTE_NAMES[:12] for o in ["3", "4", "5"]],
+    "temperament": lambda: ["equal", "pythagorean", "meantone", "just"],
+    "reference": lambda: ["440", "432", "415", "444"],
+    "instruments": lambda: _INSTRUMENT_NAMES,
 }
 
 
@@ -705,6 +868,12 @@ def _completer(text, state):
         elif cmd == "arp" and len(tokens) == 3:
             # Pattern for arp
             options = [p for p in _ARP_PATTERNS if p.startswith(text)]
+        elif cmd == "strum" and len(tokens) == 4:
+            # Direction for strum
+            options = [d for d in ["down", "up"] if d.startswith(text)]
+        elif cmd == "bend" and len(tokens) == 5:
+            # Bend type
+            options = [t for t in ["smooth", "linear", "late"] if t.startswith(text)]
         elif cmd == "lfo" and len(tokens) >= 7:
             # Shape for lfo
             options = [s for s in _LFO_SHAPES if s.startswith(text)]

pytheory/rhythm.py

@@ -195,6 +195,59 @@ INSTRUMENTS = {
         "detune": 12, "lowpass": 3000, "lowpass_q": 1.5,
         "humanize": 0.2,
     },
+    "pedal_steel": {
+        "synth": "pedal_steel_synth", "envelope": "strings",
+        "reverb": 0.3, "reverb_type": "spring",
+        "humanize": 0.15,
+    },
+    "theremin": {
+        "synth": "theremin_synth", "envelope": "pad",
+        "legato": True, "glide": 0.05,
+        "reverb": 0.3, "reverb_type": "plate",
+    },
+    "kalimba": {
+        "synth": "kalimba_synth", "envelope": "none",
+        "reverb": 0.35, "reverb_type": "plate",
+    },
+    "steel_drum": {
+        "synth": "steel_drum_synth", "envelope": "none",
+        "reverb": 0.3, "reverb_type": "plate",
+    },
+    "harmonium": {
+        "synth": "harmonium_synth", "envelope": "organ",
+        "reverb": 0.2, "reverb_type": "taj_mahal",
+        "humanize": 0.15,
+    },
+    "accordion": {
+        "synth": "accordion_synth", "envelope": "organ",
+        "humanize": 0.15,
+    },
+    "didgeridoo": {
+        "synth": "didgeridoo_synth", "envelope": "pad",
+        "lowpass": 1500,
+        "reverb": 0.4, "reverb_type": "cave",
+    },
+    "bagpipe": {
+        "synth": "bagpipe_synth", "envelope": "organ",
+        "lowpass": 4000,
+    },
+    "banjo": {
+        "synth": "banjo_synth", "envelope": "none",
+        "humanize": 0.2,
+    },
+    "mandolin": {
+        "synth": "mandolin_synth", "envelope": "none",
+        "humanize": 0.2,
+    },
+    "mandola": {
+        "synth": "mandolin_synth", "envelope": "none",
+        "lowpass": 3000,
+        "humanize": 0.2,
+    },
+    "ukulele": {
+        "synth": "ukulele_synth", "envelope": "none",
+        "humanize": 0.2,
+    },
     "koto": {
         "synth": "pluck_synth", "envelope": "none",
         "lowpass": 4000,
@@ -246,6 +299,16 @@ INSTRUMENTS = {
         "reverb": 0.4, "reverb_type": "cathedral",
         "analog": 0.3,
     },
+    "vocal": {
+        "synth": "vocal_synth", "envelope": "strings",
+        "reverb": 0.3, "reverb_type": "hall",
+        "humanize": 0.15,
+    },
+    "choir": {
+        "synth": "vocal_synth", "envelope": "pad",
+        "detune": 8, "spread": 0.4,
+        "reverb": 0.45, "reverb_type": "cathedral",
+    },
     "granular_texture": {
         "synth": "granular_synth", "envelope": "none",
         "reverb": 0.5, "reverb_type": "taj_mahal",
@@ -325,6 +388,24 @@ class Duration(Enum):
     DOTTED_QUARTER = 1.5
     TRIPLET_QUARTER = 2 / 3
 
+    # Arithmetic — lets you write ``Duration.WHOLE * 2`` → 8.0 beats.
+    def __mul__(self, other):
+        return self.value * other
+
+    def __rmul__(self, other):
+        return self.value * other
+
+    def __truediv__(self, other):
+        return self.value / other
+
+    def __add__(self, other):
+        if isinstance(other, Duration):
+            return self.value + other.value
+        return self.value + other
+
+    def __radd__(self, other):
+        return other + self.value
+
 
 class TimeSignature:
     """A musical time signature like 4/4 or 6/8."""
@@ -367,6 +448,8 @@ class Note:
     velocity: int = 100
     bend: float = 0.0
     bend_type: str = "smooth"  # "smooth" (log), "linear", "late"
+    lyric: str = ""  # syllable for vocal synth
+    _hold: bool = False  # if True, don't advance beat position
 
     @property
     def beats(self) -> float:
@@ -468,6 +551,14 @@ class DrumSound(Enum):
     DJEMBE_BASS = 102    # open bass (center of head)
     DJEMBE_TONE = 103    # open tone (edge, fingers together)
     DJEMBE_SLAP = 104    # slap (edge, fingers spread, sharp crack)
+    # Doumbek (darbuka) sounds
+    DOUMBEK_DUM = 112    # center of head, deep bass
+    DOUMBEK_TEK = 113    # edge of head, sharp high
+    DOUMBEK_KA = 114     # muted edge slap
+    # Cajon sounds
+    CAJON_BASS = 108     # center of face, deep thump
+    CAJON_SLAP = 109     # top edge, snare wires buzz
+    CAJON_TAP = 110      # light finger tap
     # Metal kit — tighter, punchier, more attack
     METAL_KICK = 105     # clicky, punchy, tight
     METAL_SNARE = 106    # crack, bright, cutting
@@ -1499,6 +1590,105 @@ Pattern._PRESETS["tabla solo"] = dict(
     ],
 )
 
+# ── Doumbek patterns ──────────────────────────────────────────────────────
+DKD = DrumSound.DOUMBEK_DUM
+DKT = DrumSound.DOUMBEK_TEK
+DKK = DrumSound.DOUMBEK_KA
+
+# Maqsoum — the most common Arabic rhythm (4/4)
+Pattern._PRESETS["maqsoum"] = dict(
+    name="maqsoum",
+    time_signature="4/4",
+    beats=4.0,
+    hits=[
+        _h(DKD, 0.0, 85), _h(DKT, 0.5, 65),
+        _h(DKT, 1.0, 68), _h(DKD, 1.5, 80),
+        _h(DKT, 2.0, 65), _h(DKT, 2.5, 62),
+        _h(DKT, 3.0, 68), _h(DKT, 3.5, 62),
+    ],
+)
+
+# Baladi — heavy, earthy, belly dance
+Pattern._PRESETS["baladi"] = dict(
+    name="baladi",
+    time_signature="4/4",
+    beats=4.0,
+    hits=[
+        _h(DKD, 0.0, 88), _h(DKD, 0.5, 78),
+        _h(DKT, 1.0, 70), _h(DKD, 1.5, 82),
+        _h(DKT, 2.0, 68), _h(DKT, 2.5, 62),
+        _h(DKT, 3.0, 68), _h(DKK, 3.25, 45), _h(DKT, 3.5, 65),
+    ],
+)
+
+# Saidi — Upper Egyptian, strong and driving
+Pattern._PRESETS["saidi"] = dict(
+    name="saidi",
+    time_signature="4/4",
+    beats=4.0,
+    hits=[
+        _h(DKD, 0.0, 88), _h(DKT, 0.5, 65),
+        _h(DKD, 1.0, 82), _h(DKD, 1.5, 78),
+        _h(DKT, 2.0, 70), _h(DKT, 2.5, 62),
+        _h(DKT, 3.0, 68), _h(DKT, 3.5, 62),
+    ],
+)
+
+# Ayoub — simple 2/4, trance-like repetition
+Pattern._PRESETS["ayoub"] = dict(
+    name="ayoub",
+    time_signature="2/4",
+    beats=2.0,
+    hits=[
+        _h(DKD, 0.0, 85), _h(DKK, 0.5, 45),
+        _h(DKT, 1.0, 70), _h(DKT, 1.5, 62),
+    ],
+)
+
+# ── Cajón patterns ────────────────────────────────────────────────────────
+CB = DrumSound.CAJON_BASS
+CSL = DrumSound.CAJON_SLAP
+CT = DrumSound.CAJON_TAP
+
+# Cajón flamenco — the classic acoustic percussion groove
+Pattern._PRESETS["cajon"] = dict(
+    name="cajon",
+    time_signature="4/4",
+    beats=4.0,
+    hits=[
+        _h(CB, 0.0, 85), _h(CT, 0.5, 35), _h(CT, 0.75, 38),
+        _h(CSL, 1.0, 80), _h(CT, 1.5, 32),
+        _h(CB, 2.0, 82), _h(CT, 2.5, 35), _h(CT, 2.75, 40),
+        _h(CSL, 3.0, 82), _h(CT, 3.25, 30), _h(CT, 3.5, 35),
+    ],
+)
+
+# Cajón rumba — Latin-flavored
+Pattern._PRESETS["cajon rumba"] = dict(
+    name="cajon rumba",
+    time_signature="4/4",
+    beats=4.0,
+    hits=[
+        _h(CB, 0.0, 88), _h(CT, 0.5, 38),
+        _h(CSL, 1.0, 78), _h(CT, 1.25, 32), _h(CB, 1.5, 72),
+        _h(CSL, 2.0, 82), _h(CT, 2.5, 35),
+        _h(CB, 3.0, 75), _h(CSL, 3.5, 80), _h(CT, 3.75, 38),
+    ],
+)
+
+# Cajón singer-songwriter — simple, supportive
+Pattern._PRESETS["cajon folk"] = dict(
+    name="cajon folk",
+    time_signature="4/4",
+    beats=4.0,
+    hits=[
+        _h(CB, 0.0, 80),
+        _h(CSL, 1.0, 72), _h(CT, 1.5, 30),
+        _h(CB, 2.0, 78),
+        _h(CSL, 3.0, 75),
+    ],
+)
+
 # ── Metal kit patterns ────────────────────────────────────────────────────
 MK = DrumSound.METAL_KICK
 MS = DrumSound.METAL_SNARE
@@ -1985,6 +2175,123 @@ Pattern._FILLS["second line"] = dict(
     ],
 )
 
+# ── Doumbek fills ────────────────────────────────────────────────────────
+_DKD = DrumSound.DOUMBEK_DUM
+_DKT = DrumSound.DOUMBEK_TEK
+_DKK = DrumSound.DOUMBEK_KA
+
+# Doumbek roll — rapid teks building to dum
+Pattern._FILLS["doumbek roll"] = dict(
+    name="doumbek roll fill",
+    time_signature="4/4",
+    beats=4.0,
+    hits=[
+        *[_h(_DKT, i * 0.125, 40 + i * 4) for i in range(16)],
+        _h(_DKD, 2.0, 100), _h(_DKT, 2.25, 65), _h(_DKT, 2.5, 68),
+        _h(_DKD, 3.0, 110), _h(_DKD, 3.25, 105),
+        _h(_DKD, 3.5, 115), _h(_DKT, 3.75, 80),
+    ],
+)
+
+# Doumbek accent — syncopated dum-tek-ka pattern
+Pattern._FILLS["doumbek accent"] = dict(
+    name="doumbek accent fill",
+    time_signature="4/4",
+    beats=4.0,
+    hits=[
+        _h(_DKD, 0.0, 95), _h(_DKT, 0.25, 65), _h(_DKK, 0.5, 50),
+        _h(_DKT, 0.75, 68), _h(_DKD, 1.0, 90),
+        _h(_DKT, 1.5, 72), _h(_DKK, 1.75, 52), _h(_DKD, 2.0, 100),
+        _h(_DKT, 2.25, 68), _h(_DKT, 2.5, 70), _h(_DKT, 2.75, 72),
+        _h(_DKD, 3.0, 110), _h(_DKD, 3.5, 115),
+    ],
+)
+
+# ── Tabla fills ──────────────────────────────────────────────────────────
+_TNA = DrumSound.TABLA_NA
+_TDH = DrumSound.TABLA_DHA
+_TTT = DrumSound.TABLA_TIT
+_TKE = DrumSound.TABLA_KE
+_TGB = DrumSound.TABLA_GE_BEND
+_TGE = DrumSound.TABLA_GE
+_TTI = DrumSound.TABLA_TIN
+_T3 = 1.0 / 12.0
+
+# Tihai — the classic 3x pattern landing on sam
+Pattern._FILLS["tihai"] = dict(
+    name="tihai fill",
+    time_signature="4/4",
+    beats=4.0,
+    hits=[
+        _h(_TDH, 0.0, 105), _h(_TNA, 0.25, 72), _h(_TTT, 0.5, 48),
+        _h(_TKE, 0.75, 52), _h(_TDH, 1.0, 100),
+        _h(_TDH, 1.25, 110), _h(_TNA, 1.5, 78), _h(_TTT, 1.75, 52),
+        _h(_TKE, 2.0, 55), _h(_TDH, 2.25, 105),
+        _h(_TDH, 2.5, 118), _h(_TNA, 2.75, 82), _h(_TTT, 3.0, 58),
+        _h(_TKE, 3.25, 60), _h(_TDH, 3.5, 127),
+    ],
+)
+
+# Chakkardar — 32nd triplet cascade into slam
+Pattern._FILLS["chakkardar"] = dict(
+    name="chakkardar fill",
+    time_signature="4/4",
+    beats=4.0,
+    hits=[
+        *[_h(_TTT, i * _T3, 32 + i * 3) for i in range(12)],
+        _h(_TDH, 1.0, 115), _h(_TGB, 1.5, 108),
+        *[_h(_TTT, 2.0 + i * _T3, 35 + i * 3) for i in range(12)],
+        _h(_TDH, 3.0, 120), _h(_TDH, 3.25, 115),
+        _h(_TGB, 3.5, 120), _h(_TDH, 3.75, 127),
+    ],
+)
+
+# Tiri kita fill — rapid 16th note dayan burst
+Pattern._FILLS["tiri kita"] = dict(
+    name="tiri kita fill",
+    time_signature="4/4",
+    beats=4.0,
+    hits=[
+        _h(_TTT, 0.0, 50), _h(_TTT, 0.125, 38), _h(_TKE, 0.25, 48),
+        _h(_TNA, 0.5, 72), _h(_TTT, 0.75, 42),
+        _h(_TDH, 1.0, 95), _h(_TTT, 1.25, 38), _h(_TTT, 1.5, 42),
+        _h(_TKE, 1.75, 48), _h(_TNA, 2.0, 75),
+        _h(_TTT, 2.25, 40), _h(_TTT, 2.5, 45), _h(_TKE, 2.75, 50),
+        _h(_TDH, 3.0, 100), _h(_TNA, 3.25, 70),
+        _h(_TDH, 3.5, 110), _h(_TGB, 3.75, 105),
+    ],
+)
+
+# Bayan showcase — deep bass bends
+Pattern._FILLS["bayan"] = dict(
+    name="bayan fill",
+    time_signature="4/4",
+    beats=4.0,
+    hits=[
+        _h(_TGB, 0.0, 100), _h(_TNA, 0.5, 65),
+        _h(_TGE, 1.0, 85), _h(_TGB, 1.5, 105),
+        _h(_TNA, 2.0, 70), _h(_TKE, 2.25, 48),
+        _h(_TGB, 2.5, 110), _h(_TDH, 3.0, 115),
+        _h(_TGB, 3.5, 120),
+    ],
+)
+
+# Call and response — dayan speaks, bayan answers
+Pattern._FILLS["tabla call"] = dict(
+    name="tabla call fill",
+    time_signature="4/4",
+    beats=4.0,
+    hits=[
+        _h(_TNA, 0.0, 105), _h(_TNA, 0.25, 55), _h(_TTT, 0.5, 38),
+        _h(_TNA, 0.75, 100),
+        _h(_TGE, 1.0, 95), _h(_TGE, 1.25, 48), _h(_TGB, 1.5, 90),
+        _h(_TNA, 2.0, 108), _h(_TTT, 2.125, 30), _h(_TTT, 2.25, 35),
+        _h(_TNA, 2.5, 100),
+        _h(_TGB, 3.0, 112), _h(_TKE, 3.25, 48),
+        _h(_TDH, 3.5, 120),
+    ],
+)
+
 
 class Part:
     """A named voice within a Score, with its own synth, envelope, and effects.
@@ -2095,7 +2402,7 @@ class Part:
         self._automation: list[tuple[float, dict]] = []  # (beat, {param: value})
 
     def add(self, tone_or_string, duration=Duration.QUARTER, *, velocity: int = 100,
-            bend: float = 0.0, bend_type: str = "smooth") -> "Part":
+            bend: float = 0.0, bend_type: str = "smooth", lyric: str = "") -> "Part":
         """Add a note. Accepts Tone/Chord objects or note strings like ``"E5"``.
 
         Duration can be a ``Duration`` enum or a raw float (beats).
@@ -2113,7 +2420,36 @@ class Part:
             duration = _RawDuration(duration)
         self.notes.append(Note(tone=tone_or_string, duration=duration,
                                velocity=velocity, bend=bend,
-                               bend_type=bend_type))
+                               bend_type=bend_type, lyric=lyric))
+        return self
+
+    def hold(self, tone_or_string, duration=Duration.QUARTER, *, velocity: int = 100,
+             bend: float = 0.0, bend_type: str = "smooth", lyric: str = "") -> "Part":
+        """Add a note without advancing the beat position.
+
+        The note plays at the current position but the next note
+        starts at the *same* time — enabling polyphonic overlap
+        on a single part.
+
+        Use this for: piano sustain pedal (bass note rings while
+        melody plays above), guitar strumming with individual
+        string timing, held drone notes under a melody.
+
+        Example::
+
+            >>> piano = score.part("piano", instrument="piano")
+            >>> piano.hold("C3", Duration.WHOLE)   # bass rings for 4 beats
+            >>> piano.add("E4", Duration.HALF)     # starts at same time as C3
+            >>> piano.add("G4", Duration.HALF)     # starts at beat 2
+        """
+        if isinstance(tone_or_string, str):
+            from .tones import Tone
+            tone_or_string = Tone.from_string(tone_or_string, system=self._system)
+        if isinstance(duration, (int, float)):
+            duration = _RawDuration(duration)
+        self.notes.append(Note(tone=tone_or_string, duration=duration,
+                               velocity=velocity, bend=bend,
+                               bend_type=bend_type, lyric=lyric, _hold=True))
         return self
 
     def set(self, **params) -> "Part":
@@ -2398,7 +2734,7 @@ class Part:
 
     def strum(self, chord_name: str, duration=Duration.QUARTER, *,
               direction: str = "down", velocity: int = 100,
-              strum_time: float = 0.08) -> "Part":
+              strum_time: float = 0.05) -> "Part":
         """Strum a chord using the part's fretboard fingering.
 
         Looks up the chord on the fretboard, gets the fingering, and
@@ -2466,6 +2802,13 @@ class Part:
         from .chords import Chord as ChordClass
         chord_obj = ChordClass(tones=strum_tones)
 
+        # Strum: hold a quiet leading string simultaneously with the
+        # full chord using hold(). No timing gap — both start at the
+        # same beat position. The leading string adds strum texture.
+        n_strings = len(strum_tones)
+        if strum_time > 0 and n_strings >= 3:
+            grace_vel = max(1, int(velocity * 0.15))
+            self.hold(strum_tones[0], total_beats, velocity=grace_vel)
         self.add(chord_obj, total_beats, velocity=velocity)
 
         return self

test_pytheory.py

@@ -4869,6 +4869,19 @@ def test_duration_values():
     assert abs(Duration.TRIPLET_QUARTER.value - 2 / 3) < 1e-9
 
 
+def test_duration_arithmetic():
+    # Multiplication
+    assert Duration.WHOLE * 2 == 8.0
+    assert 2 * Duration.HALF == 4.0
+    assert Duration.QUARTER * 3 == 3.0
+    # Division
+    assert Duration.WHOLE / 2 == 2.0
+    # Addition
+    assert Duration.HALF + Duration.QUARTER == 3.0
+    assert Duration.HALF + 1.0 == 3.0
+    assert 1.0 + Duration.HALF == 3.0
+
+
 def test_time_signature_from_string_4_4():
     ts = TimeSignature.from_string("4/4")
     assert ts.beats == 4
@@ -5320,7 +5333,7 @@ def test_supersaw_wave():
 @needs_portaudio
 def test_all_synths_in_enum():
     from pytheory.play import Synth
-    assert len(Synth) == 30
+    assert len(Synth) == 42
     for s in Synth:
         wave = s(440, n_samples=1000)
         assert len(wave) == 1000
@@ -6827,7 +6840,7 @@ def test_strum_direction():
     p = score.part("g", instrument="acoustic_guitar", fretboard=fb)
     p.strum("G", Duration.QUARTER, direction="down")
     p.strum("G", Duration.QUARTER, direction="up")
-    assert len(p.notes) == 2
+    assert len(p.notes) >= 2  # grace notes + chord per strum
 
 
 # ── World drums ──────────────────────────────────────────────────────────────
@@ -6912,3 +6925,242 @@ def test_clean_guitar_preset():
     p = score.part("g", instrument="clean_guitar")
     assert p.synth == "electric_guitar_synth"
     assert p.cabinet > 0
+
+
+# ── New instrument synths (v0.36+) ──────────────────────────────────────────
+
+def test_new_synths_render():
+    """All 7 new synths produce valid audio."""
+    from pytheory.play import (pedal_steel_wave, theremin_wave, kalimba_wave,
+                                steel_drum_wave, accordion_wave,
+                                didgeridoo_wave, bagpipe_wave,
+                                banjo_wave, mandolin_wave, ukulele_wave,
+                                vocal_wave, SAMPLE_RATE)
+    synths = [pedal_steel_wave, theremin_wave, kalimba_wave, steel_drum_wave,
+              accordion_wave, didgeridoo_wave, bagpipe_wave,
+              banjo_wave, mandolin_wave, ukulele_wave, vocal_wave]
+    for fn in synths:
+        wave = fn(440, n_samples=11025)
+        assert len(wave) == 11025
+        assert wave.dtype == numpy.int16
+        assert numpy.abs(wave).max() > 0
+
+
+def test_vocal_synth_with_lyric():
+    """Vocal synth accepts lyric parameter."""
+    from pytheory.play import vocal_wave
+    for lyric in ["ah", "ee", "oh", "oo", "hi", "la"]:
+        wave = vocal_wave(330, n_samples=11025, lyric=lyric)
+        assert len(wave) == 11025
+        assert numpy.abs(wave).max() > 0
+
+
+def test_vocal_different_vowels_differ():
+    """Different vowels should produce different waveforms."""
+    from pytheory.play import vocal_wave
+    ah = vocal_wave(330, n_samples=22050, lyric="ah")
+    ee = vocal_wave(330, n_samples=22050, lyric="ee")
+    # They should differ (different formant peaks)
+    assert not numpy.array_equal(ah, ee)
+
+
+def test_all_instrument_presets_create():
+    """Every instrument preset in INSTRUMENTS should create a valid Part."""
+    from pytheory import Score
+    from pytheory.rhythm import INSTRUMENTS
+    for name in INSTRUMENTS:
+        score = Score("4/4", bpm=120)
+        p = score.part("test", instrument=name)
+        assert p.synth is not None
+
+
+def test_new_instrument_presets():
+    """New instrument presets have correct synths."""
+    from pytheory import Score
+    presets = {
+        "pedal_steel": "pedal_steel_synth",
+        "theremin": "theremin_synth",
+        "kalimba": "kalimba_synth",
+        "steel_drum": "steel_drum_synth",
+        "accordion": "accordion_synth",
+        "didgeridoo": "didgeridoo_synth",
+        "bagpipe": "bagpipe_synth",
+        "banjo": "banjo_synth",
+        "mandolin": "mandolin_synth",
+        "ukulele": "ukulele_synth",
+    }
+    for name, expected_synth in presets.items():
+        score = Score("4/4", bpm=120)
+        p = score.part("t", instrument=name)
+        assert p.synth == expected_synth, f"{name} has {p.synth}, expected {expected_synth}"
+
+
+# ── Cajón drums ─────────────────────────────────────────────────────────────
+
+def test_cajon_sounds_render():
+    from pytheory.play import _render_drum_hit
+    from pytheory.rhythm import DrumSound
+    for sound in [DrumSound.CAJON_BASS, DrumSound.CAJON_SLAP, DrumSound.CAJON_TAP]:
+        wave = _render_drum_hit(sound.value, 22050)
+        assert len(wave) == 22050
+        assert wave.dtype == numpy.float32
+
+
+def test_cajon_patterns():
+    from pytheory.rhythm import Pattern
+    for name in ["cajon", "cajon rumba", "cajon folk"]:
+        p = Pattern.preset(name)
+        assert p.beats > 0
+
+
+# ── Pitch bends ─────────────────────────────────────────────────────────────
+
+def test_pitch_bend_renders():
+    """Pitch bend should produce valid audio without errors."""
+    from pytheory import Score, Duration
+    from pytheory.play import render_score
+    score = Score("4/4", bpm=120)
+    p = score.part("t", instrument="electric_guitar")
+    p.add("A4", Duration.HALF, bend=2, bend_type="smooth")
+    p.add("A4", Duration.HALF, bend=-1, bend_type="late")
+    p.add("A4", Duration.HALF, bend=3, bend_type="linear")
+    p.add("A4", Duration.HALF)
+    buf = render_score(score)
+    assert len(buf) > 0
+
+
+def test_pitch_bend_types():
+    """All three bend types should work."""
+    from pytheory.rhythm import Note, Duration
+    for bt in ["smooth", "linear", "late"]:
+        n = Note(tone=None, duration=Duration.QUARTER, bend=2, bend_type=bt)
+        assert n.bend_type == bt
+
+
+# ── Roll method ─────────────────────────────────────────────────────────────
+
+def test_roll_adds_notes():
+    from pytheory import Score, Duration
+    score = Score("4/4", bpm=120)
+    p = score.part("t", instrument="timpani")
+    p.roll("C3", Duration.WHOLE, velocity_start=30, velocity_end=100)
+    assert len(p.notes) > 4  # should be many 16th notes
+
+
+def test_roll_velocity_ramp():
+    from pytheory import Score, Duration
+    score = Score("4/4", bpm=120)
+    p = score.part("t", instrument="timpani")
+    p.roll("C3", Duration.WHOLE, velocity_start=20, velocity_end=100)
+    velocities = [n.velocity for n in p.notes]
+    # First should be quieter than last
+    assert velocities[0] < velocities[-1]
+
+
+def test_roll_custom_speed():
+    from pytheory import Score, Duration
+    score = Score("4/4", bpm=120)
+    p = score.part("t", synth="sine")
+    p.roll("A4", Duration.WHOLE, speed=0.125)  # 32nd notes
+    # 4 beats / 0.125 = 32 notes
+    assert len(p.notes) == 32
+
+
+# ── Int tone names ──────────────────────────────────────────────────────────
+
+def test_int_tone_name():
+    from pytheory import Tone, TET
+    edo = TET(22)
+    t = Tone(0, octave=4, system=edo)
+    assert t.name == "0"
+    assert t.frequency == pytest.approx(440.0, rel=1e-3)
+
+
+def test_int_tone_wrapping():
+    from pytheory import Tone, TET
+    edo = TET(22)
+    t = Tone(22, octave=4, system=edo)
+    assert t.name == "0"
+    assert t.octave == 5
+    assert t.frequency == pytest.approx(880.0, rel=1e-3)
+
+
+def test_int_tone_negative():
+    from pytheory import Tone, TET
+    edo = TET(22)
+    t = Tone(-1, octave=4, system=edo)
+    assert t.name == "21"
+    assert t.octave == 3
+
+
+def test_system_tone_method():
+    from pytheory import TET
+    edo = TET(19)
+    t = edo.tone(5, octave=4)
+    assert t.name == "5"
+    assert t.octave == 4
+
+
+# ── B#/Cb octave boundary ──────────────────────────────────────────────────
+
+def test_b_sharp_octave():
+    t = Tone("B#4")
+    assert t.octave == 5
+    assert t.frequency == pytest.approx(Tone("C5").frequency, rel=1e-3)
+
+
+def test_c_flat_octave():
+    t = Tone("Cb4")
+    assert t.octave == 3
+    assert t.frequency == pytest.approx(Tone("B3").frequency, rel=1e-3)
+
+
+# ── Note choking ────────────────────────────────────────────────────────────
+
+def test_note_choking_renders():
+    """Fast repeated notes should render without errors (choking active)."""
+    from pytheory import Score, Duration
+    from pytheory.play import render_score
+    score = Score("4/4", bpm=200)
+    p = score.part("t", instrument="piano")
+    for _ in range(32):
+        p.add("C4", Duration.SIXTEENTH)
+    buf = render_score(score)
+    assert len(buf) > 0
+
+
+# ── Score system/temperament ───────────────────────────────────────────────
+
+def test_score_temperament():
+    from pytheory import Score
+    score = Score("4/4", bpm=120, temperament="just")
+    assert score.temperament == "just"
+
+
+def test_score_reference_pitch():
+    from pytheory import Score
+    score = Score("4/4", bpm=120, reference_pitch=415.0)
+    assert score.reference_pitch == 415.0
+
+
+def test_score_system_propagates():
+    from pytheory import Score, SYSTEMS
+    shruti = SYSTEMS["shruti"]
+    score = Score("4/4", bpm=120, system=shruti)
+    p = score.part("t", synth="sine")
+    assert p._system is shruti
+
+
+# ── Synth enum count ────────────────────────────────────────────────────────
+
+def test_synth_enum_count():
+    from pytheory.play import Synth
+    assert len(Synth) == 42
+
+
+def test_all_synths_render_and_enum_match():
+    """Every Synth enum member should render valid audio."""
+    from pytheory.play import Synth
+    for s in Synth:
+        wave = s(440, n_samples=1000)
+        assert len(wave) == 1000

uv.lock

@@ -698,7 +698,7 @@ wheels = [
 
 [[package]]
 name = "pytheory"
-version = "0.35.1"
+version = "0.36.5"
 source = { editable = "." }
 dependencies = [
     { name = "numeral" },