cascadevad-onnx 0.1.0

Load arbitrary Voice Activity Detection (VAD) models behind a unified ONNX API

cascadevad

Load arbitrary Voice Activity Detection models behind a single, unified API — every model runs through ONNX Runtime. One streaming/​batch interface, one audio-format story, pluggable models.

from cascadevad import load_vad

vad = load_vad("silero")                              # bundled, works fully offline
prob = vad.process_chunk(pcm_bytes)                   # streaming → float in [0, 1]
segments = vad.get_speech_segments(audio, sample_rate=16000)
# -> [SpeechSegment(start=0.32, end=2.27), SpeechSegment(start=3.27, end=4.45), ...]

Why

Every VAD ships its own loader, audio format, feature pipeline and state handling. cascadevad hides that behind one VADModel interface: feed it audio (raw int16 bytes, numpy arrays, any sample rate) and get back per-frame speech probabilities or ready-made speech segments. Models are described declaratively by an IOSignature, so a single generic engine drives most of them and you can point the same API at any custom .onnx file.

• Lightweight runtime — only numpy, onnxruntime, huggingface_hub.
• Offline by default — a small Silero model is bundled in the wheel.
• Streaming and batch — process_chunk() for live audio, get_speech_segments() / probabilities() for whole buffers.
• Bring your own model — load any ONNX VAD by path/URL with a signature.
• Extensible — third parties register backends/models via entry points.

Install

uv pip install cascadevad-onnx          # runtime (numpy + onnxruntime + huggingface_hub)
uv pip install "cascadevad-onnx[mic]"   # + microphone examples

Models

name	rate	parity vs upstream	notes
silero / silero-8k / silero-op15	16k / 8k / 16k	MAE 0	bundled default, raw PCM
marblenet / marblenet-int8	16k	MAE 4e-4	NVIDIA NeMo Frame-VAD, multilingual (license)
pyannote / pyannote-int8	16k	MAE 0	pyannote segmentation-3.0, windowed
fsmn / fsmn-quant	16k	tracks upstream	FunASR FSMN-VAD; needs cascadevad-onnx[fsmn]
speechbrain	16k	MAE 0	SpeechBrain CRDNN, LibriParty-trained
ten	16k	—	feature extractor provided by TEN's native library

See docs/backends.md for per-model detail and the benchmark for measured comparisons across datasets, including WebRTC and energy baselines.

Models other than the bundled Silero are downloaded on first use from the aryashah00/cascadevad-models HuggingFace repo and cached under $XDG_DATA_HOME/cascadevad. See docs/backends.md for per-model detail and parity notes.

CLI

cascadevad list                       # list available models
cascadevad probe silero               # print a model's ONNX input/output signature
cascadevad segment speech.wav         # print detected speech segments of a WAV

Documentation

• Quickstart
• Streaming
• Custom models & IOSignature
• Backends & parity notes
• Plugins
• Model conversion
• Licensing
• API reference

License

Apache-2.0. Bundled/downloaded model weights retain their upstream licenses — see docs/licensing.md.