Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
Offline multi-speaker meeting-speech toolkit: planted-ground-truth synthetic meeting factory, VAD, speaker embeddings, diarization (AHC/spectral/VB-HMM), overlap detection, CTC speaker-attributed ASR, cpWER/DER/JER evaluation, online streaming mode, deterministic reports. NumPy core, CPU-only torch extra.
A PyTorch-based Speech Toolkit
Silero VAD: pre-trained enterprise-grade Voice Activity Detector
Multilingual Automatic Speech Recognition with word-level timestamps and confidence
Voice Activity Detector (VAD) : low-latency, high-performance and lightweight
A curated list of awesome Speaker Diarization papers, libraries, datasets, and other resources.
Controllable Transcription. Verbatim ( every, filler, pause, stutter, vocal sound) , or intended ( what the speaker meant to say, optimized for readability) with word-level timestamps.
You can find the speech algorithms you want here
Ultra-tiny 2.1k streaming voice activity detector (2.1 KB INT8). 200 ms window for microcontrollers, edge devices, and DSPs. ships with ONNX, TorchScript, and standalone C header.