mravanelli/SincNet

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1243 stars · 272 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

SincNet is a PyTorch neural architecture that processes raw audio waveforms using parametrized sinc band-pass filters in the first convolutional layer. The repository provides code and utilities for speaker identification, with a TIMIT example included.

Use cases

• speaker identification from raw audio waveforms
• speaker verification with deep learning
• learn customized filter banks for audio tasks
• run speaker recognition experiments on TIMIT
• process raw audio samples with CNNs instead of spectrograms
• research learnable front-end filters for speech models

When to choose

• you want to learn filters directly from raw waveforms rather than hand-crafted spectrogram features
• you need a compact parametrized band-pass filter bank tuned to your audio application
• you are doing speaker recognition research and want a well-known reference implementation

When to avoid

• you need a maintained general-purpose speech toolkit - consider SpeechBrain or PyTorch-Kaldi instead
• you want production-ready ASR rather than a research showcase
• you work outside Linux or need recent PyTorch version support

Facets

library · maturity maintenance

audio-processing machine-learning deep-learning speech-recognition speech-processing deep-learning machine-learning artificial-intelligence python sinc-filters raw-waveform speaker-recognition cnn pytorch timit digital-signal-processing speaker-verification audio linux gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="mravanelli/SincNet")