Differentiable wavetable synthesizer

A system, comprising:

• at least one processor;
• and
• at least one memory communicatively coupled to the at least one processor and storing instructions that upon execution by the at least one processor cause the system to perform operations, the operations comprising:
• extracting features from a dataset of sounds, wherein the features comprise at least timbre embedding;
• input the features to a first machine learning model, wherein the first machine learning model is configured to extract a set of N×L learnable parameters, N represents a number of wavetables, and L represents a wavetable length;
• and
• outputting a plurality of wavetables, wherein each of plurality of wavetables comprises a waveform associated with a unique timbre, wherein the plurality of wavetables form a dictionary, and wherein the plurality of wavetables are portable to perform audio-related tasks.

A non-transitory computer-readable storage medium, storing computer-readable instructions that upon execution by a processor cause the processor to implement operations, the operation comprising:

• extracting features from a dataset of sounds, wherein the features comprise at least timbre embedding;
• input the features to a first machine learning model, wherein the first machine learning model is configured to extract a set of N×L learnable parameters, N represents a number of wavetables, and L represents a wavetable length;
• and
• outputting a plurality of wavetables, wherein each of plurality of wavetables comprises a waveform associated with a unique timbre, wherein the plurality of wavetables form a dictionary, and wherein the plurality of wavetables are portable to perform audio-related tasks.