Let’s write a wavetable synthesizer in Python!

This article is a follow-up to the article on wavetable synthesis theory. Here we will implement the algorithms explained there. Please refer back to that article if you find some background information missing.

Below is the listing containing a wavetable synthesizer implemented in Python.

Sound is generated by calling the synthesize() method of a Voice class object. Voice objects are monophonic (can play just 1 pitch at a time) and contain arbitrarily many oscillators whose outputs are summed together. We can think of it as creating “layers” of timbre. 1 oscillator = 1 periodic waveform.

Voice’s oscillators can be arbitrary oscillators but in this implementation we use wavetable oscillators as represented by the WavetableOscillator class.

WavetableOscillator objects have a set frequency and generate sound by looping over a wave table. wavetable_index gets incremented with each sample produced by the getSample() method. The increment depends on the frequency, sampling rate and wave table length.

The main() function in the listing below synthesizes a sine waveform, a sawtooth waveform, a multi-cycle waveform, a mixture-of-gaussians waveform, and the same waveform but with a frequency changed exponentially from 20 Hz to 3000 Hz and back over a time period of 20 seconds. All synthesized sounds are saved in the working directory “wavetable-synthesis-python”.

Should you have any questions, please, write a comment below!

View the code on GitHub

import numpy as np
from pathlib import Path
from scipy.io import wavfile

class LinearInterpolator():
    def __call__(self, values, index):
        """Interpolate linearly between values closest to index."""
        # Closest index value smaller or equal to index
        low = int(index)

        # Closest index value larger than index
        high = int(np.ceil(index))

        # Handle integer index
        if low == high:
            return values[low]

        # Return the weighted sum
        return (index - low) * values[high %
                                      values.shape[0]] + (high - index) * values[low]

class ZeroOrderInterpolator():
    def __call__(self, values, index):
        Return the value in values at the largest integer index
        smaller or equal to index.
        return values[int(index)]

class WavetableOscillator:
    Oscillator generates samples based on current frequency.
    If frequency is 0, no samples are produced.

    WavetableOscillator uses wavetable synthesis to generate each sample.
    To this end, it needs a wavetable, the sampling rate 
    and the interpolation method used.

    def __init__(self, wavetable, sampling_rate, interpolator):
        self.wavetable = wavetable
        self.sampling_rate = sampling_rate
        self.interpolator = interpolator
        self.wavetable_index = 0.0
        self.__frequency = 0

    def fill(self, audio_block, from_index=0, to_index=-1):
        """Fill audio_block in [from_index, to_index) range."""
        for i in range(from_index, to_index % audio_block.shape[0]):
            audio_block[i] = self.get_sample()
        return audio_block

    def get_sample(self):
        """Return 1 oscillator sample."""
        sample = self.interpolator(self.wavetable, self.wavetable_index)
        self.wavetable_index = (
            self.wavetable_index + self.wavetable_increment) % self.wavetable.shape[0]
        return sample

    def frequency(self):
        return self.__frequency

    def frequency(self, value):
        self.__frequency = value
        self.wavetable_increment = self.wavetable.shape[0] * \
            self.frequency / self.sampling_rate
        if self.frequency <= 0:
            self.wavetable_index = 0.0

class Voice:
    Main class to generate sound.

    1 Voice object corresponds to 1 pitch played.

    oscillators: list
        list containing the oscillators that generate sound
    gain: float
        amplitude in dBFS of the generated signal

    def __init__(self, sampling_rate, gain=-20):
        self.sampling_rate = sampling_rate
        self.gain = gain
        self.oscillators = []

    def synthesize(self, frequency, duration_seconds):
        Generate duration_seconds of samples at the 
        specified frequency.
        buffer = np.zeros((duration_seconds * self.sampling_rate,))
        if np.isscalar(frequency):
            frequency = np.ones_like(buffer) * frequency

        for i in range(len(buffer)):
            for oscillator in self.oscillators:
                oscillator.frequency = frequency[i]
                buffer[i] += oscillator.get_sample()
        amplitude = 10 ** (self.gain / 20)
        buffer *= amplitude
        buffer = fade_in_out(buffer)
        return buffer

def fade_in_out(signal, fade_length=1000):
    Apply a half-cosine window to first and 
    last fade_length samples of signal.
    fade_in_envelope = (1 - np.cos(np.linspace(0, np.pi, fade_length))) * 0.5
    fade_out_envelope = np.flip(fade_in_envelope)

    # Handle 2-channel audio
    if signal.ndim == 2:
        fade_in_envelope = fade_in_envelope[:, np.newaxis]
        fade_out_envelope = fade_out_envelope[:, np.newaxis]

    # Apply fade-in
    signal[:fade_length, ...] = np.multiply(
        signal[:fade_length, ...], fade_in_envelope)

    # Apply fade-out
    signal[-fade_length:, ...] = np.multiply(
        signal[-fade_length:, ...], fade_out_envelope)

    return signal

def generate_wavetable(length, f):
    Generate a wavetable of specified length using 
    function f(x) where x is phase.
    Period of f is assumed to be 2 pi.
    wavetable = np.zeros((length,), dtype=np.float32)
    for i in range(length):
        wavetable[i] = f(2 * np.pi * i / length)
    return wavetable

def output_wavs(signal, name, sampling_rate, table):
    """Save the signal and wave table under specified names."""
    output_dir = Path('wavetable-synthesis-python')
    output_dir.mkdir(parents=True, exist_ok=True)

        output_dir /
        output_dir /

def gaussian_mixture(x):
    """Sum of 5 Gaussians roughly in [0,2pi) range."""
    return np.exp(-3 * (x - 1)**2) \
        - 0.4 * np.exp(-3 * (x - 2.3)**2) \
        + 0.8 * np.exp(-10 * (x - 3.3)**2) \
        - np.exp(-7 * (x - 4.5)**2) \
        + 0.3 * np.exp(-2 * (x - 5)**2)

def generate_gaussians_table(wavetable_size):
    """Generate the wave table with 5 Gaussians."""
    gaussians_table = generate_wavetable(wavetable_size, gaussian_mixture)

    # Subtract the DC component
    gaussians_table -= np.mean(gaussians_table)

    # Smooth out at the edges so that 
    # the wave table starts and ends around 0.0
    gaussians_table = fade_in_out(gaussians_table, 5)
    return gaussians_table

def sawtooth_waveform(x):
    """Sawtooth with period 2 pi."""
    return (x + np.pi) / np.pi % 2 - 1

def square_waveform(x):
    """Square waveform with period 2 pi."""
    return np.sign(np.sin(x))

def main():
    # Global parameters
    sampling_rate = 44100
    wavetable_size = 64

    # Create a mono synth
    synth = Voice(sampling_rate, gain=-20)

    ### Sine generation ###
    sine_table = generate_wavetable(wavetable_size, np.sin)
    # Add an oscillator
    synth.oscillators += [
    # Synthesize sound
    sine = synth.synthesize(frequency=440, duration_seconds=5)
    # Save the output
    output_wavs(sine, 'sine', sampling_rate, sine_table)

    ### Sawtooth generation ###
    sawtooth_table = generate_wavetable(wavetable_size, sawtooth_waveform)
    synth.oscillators[0] = WavetableOscillator(
        sawtooth_table, sampling_rate, LinearInterpolator())
    sawtooth_signal = synth.synthesize(frequency=440, duration_seconds=5)
    output_wavs(sawtooth_signal, 'sawtooth', sampling_rate, sawtooth_table)

    sawtooth880 = synth.synthesize(frequency=880, duration_seconds=5)
    output_wavs(sawtooth880, 'sawtooth880', sampling_rate, sawtooth_table)

    ### Multi-cycle waveform generation ###
    square_table = generate_wavetable(wavetable_size, square_waveform)
    multi_cycle_table = np.concatenate(
        (sine_table, square_table, sawtooth_table))
    synth.oscillators[0] = WavetableOscillator(
        multi_cycle_table, sampling_rate, LinearInterpolator())
    # Frequency is divided by 3 because we concatenated 3 tables
    multi_cycle = synth.synthesize(frequency=330 / 3, duration_seconds=5)
    output_wavs(multi_cycle, 'multi_cycle', sampling_rate, multi_cycle_table)

    ### Gaussian mixture generation ###
    gaussians_table = generate_gaussians_table(wavetable_size)
    synth.oscillators[0] = WavetableOscillator(
        gaussians_table, sampling_rate, LinearInterpolator())
    gaussians_waveform = synth.synthesize(frequency=110, duration_seconds=5)

    ### Continuous frequency control ###
    # We want to generate and exponentially swept frequency vector.
    # Frequency will start at min_frequency, reach max_frequency after
    # half of the duration and then fall back to min_frequency.
    duration = 20
    min_frequency = 20
    max_frequency = 3000

    # Calculate the base of the exponent
    base = (max_frequency / min_frequency) ** (1 /
                                               (duration // 2 * sampling_rate))

    # Calculate the exponential frequency sweep on the rising slope
    instantaneous_frequency_half = min_frequency * \
        base ** np.arange(0, duration // 2 * sampling_rate, 1)

    # Make the falling slope the reverse of the first slope
    instantaneous_frequency = np.concatenate(
        (instantaneous_frequency_half, np.flip(instantaneous_frequency_half)))

    # Add tiny oscillations around the intantaneous frequency
    instantaneous_frequency += np.multiply(instantaneous_frequency,
                                           np.random.default_rng().uniform(-0.1, 0.1, size=instantaneous_frequency.shape))

    # Synthesize on a sample-by-sample basis and output
    signal_with_varying_frequency = synth.synthesize(
        frequency=instantaneous_frequency, duration_seconds=duration)

if __name__ == '__main__':

Up next: Wavetable synth implementation in the JUCE C++ framework and Rust!