audio-dsp 0.1.10

Python audio DSP library for synthesis, effects, and sequencing

audio-dsp

A Python audio DSP library for synthesis, effects, and sequencing.

Installation

# Core installation (numpy, scipy, soundfile)
pip install audio-dsp

# Full installation with all optional dependencies
pip install audio-dsp[full]

# Specific extras
pip install audio-dsp[synth]   # Synthesis modules
pip install audio-dsp[midi]    # MIDI processing
pip install audio-dsp[ml]      # Machine learning features
pip install audio-dsp[viz]     # Visualization
pip install audio-dsp[audio]   # Extended audio processing (librosa, pydub)

Features

Synthesizers (audio_dsp.synth)

• SubtractiveSynth - Classic subtractive synthesis with oscillators, filters, LFO, ADSR
• DX7FMSynth - DX7-style FM synthesis with 4 operators and 5 algorithms
• PhysicalModelingSynth - Physical modeling synthesis
• DrumSynth - Drum synthesis
• ChipTone functions - Retro 8-bit chip synthesis (kick, snare, blip, etc.)
• PluckSynth - Karplus-Strong plucked string synthesis
• DialupSynth - Modem/dial-up sound synthesis

Effects (audio_dsp.effects)

All effects follow a unified API: effect(signal, sample_rate, **params) → numpy.ndarray

• Dynamics: compress, multi-band saturation, sidechain compressor
• Filters: filter (lowpass, bandpass)
• Modulation: phaser_flanger, chorus, flutter, pitch drift
• Time-based: delay, reverb (convolution), time slice
• Spectral: Frequency splicer, melt spectrum, vocoder, spectral quantization
• Character: Distortion (19 types), lofi, glitch, tape saturation
• Specialized: autotune, sitar sympathetic resonance, variable_quantizer

Sequencers (audio_dsp.sequencer)

Unified API - All sequencers share a common interface:

• BaseSequencer - Base class with generate(), export() methods
• PatternSequencer - Pattern-based sequencing with samples
• LiquidSequencer - Non-linear timing with swing/jitter
• SampleManager - Load samples from files or numpy arrays

Specialized Sequencers:

• RagaSequencer - Indian classical music with time-of-day raga selection
• TreeSequencer - Tree traversal-based algorithmic composition
• ChordProgressionSequencer - Microtonal chord progressions (24-TET, etc.)
• MelodySequencer - Melody development with counterpoint generation
• Game of Life sequencers with video output
• Matrix composer for linear algebra sonification

MIDI (audio_dsp.midi)

• Polyrhythmic MIDI generation
• MIDI file looping
• Alternate tuning systems
• Logarithmic tunings

Utilities (audio_dsp.utils)

• Audio I/O - Lightweight audio loading/saving with built-in WAV support (no external dependencies)
• Scale and melody utilities
• Spectral analysis
• Transient extraction
• Maqamat (Arabic scales)
• Noise algorithms
• Image to audio conversion

Quick Start

Notebook	Description	Link
00. Quickstart	Generate your first sound in 30 seconds.
01. Synthesizers	Deep dive into Oscillators, FM, and Envelopes.
02. Effects Rack	How to chain Reverb, Delay, and Distortion.
03. Sequencing	creating generative melodies and MIDI tools.
04. Utilities	Audio file handling and analysis tools.

from audio_dsp.synth import SubtractiveSynth
import soundfile as sf

# Create a subtractive synth
synth = SubtractiveSynth(sample_rate=44100)
synth.osc_wave = "saw"
synth.filter_cutoff = 800
synth.filter_resonance = 2.0

# Synthesize a note
audio = synth.synthesize(freq=220, duration=2.0)

# Save to file
sf.write("output.wav", audio, 44100)

from audio_dsp.utils import load_audio
from audio_dsp.utils import wav_io
from audio_dsp.effects import filter, delay, reverb, compress

# Load audio
sr, audio = load_audio("input.wav", mono=True)

# Chain effects - all work on numpy arrays
audio = filter(audio, sr, cutoff=1000, filter_type="lowpass")
audio = delay(audio, sr, delay_time=0.25, feedback=0.5, mode="analog")
audio = reverb(audio, "impulse.wav", sr, wet_mix=0.3)
audio = compress(audio, sr, threshold=-20, ratio=4.0)

# Save output
wav_io.write("output.wav", sr, audio.astype('float32'))

from audio_dsp.sequencer import PatternSequencer, SampleManager
from audio_dsp.synth import SubtractiveSynth
import numpy as np

# Create samples from synth output
synth = SubtractiveSynth()
kick = synth.synthesize(freq=60, duration=0.1)
snare = synth.synthesize(freq=200, duration=0.1)

# Create pattern sequencer
seq = PatternSequencer(bpm=120)
seq.add_sample("kick", kick)    # numpy array
seq.add_sample("snare", snare)
seq.add_sample("hihat", "samples/hihat.wav")  # or file path

# Generate from patterns
patterns = {
    "kick": "1000100010001000",
    "snare": "0000100000001000",
    "hihat": "1010101010101010"
}
audio = seq.generate_from_patterns(patterns, duration=4.0)

from audio_dsp.sequencer import RagaSequencer

# Generate raga-based music appropriate for time of day
seq = RagaSequencer(bpm=90, root_frequency=220.0)
raga = seq.choose_raga()  # Selects based on current hour
print(f"Playing {raga['name']}")

audio = seq.generate_raga_phrase(raga, duration=30.0)

License

MIT License - see LICENSE for details.