Feature Request
Owl is a great personal wearable AI that runs locally. Suggesting SenseVoice as an ASR option — its compact size and speed make it ideal for local/edge deployment.
Why SenseVoice for wearable AI?
- 234M params — compact enough for local inference on consumer hardware
- Non-autoregressive — constant low latency (~100ms), no waiting for sequential decoding
- 5x faster than Whisper — better battery life and responsiveness
- 50+ languages — single model handles any language
- Emotion detection — contextual awareness of speaker mood
- Audio events — detects environmental sounds (laughter, music, etc.)
Local deployment options
- Python (simplest):
pip install funasr
- ONNX (optimized): via Sherpa-ONNX — supports ARM, x86, mobile
- C++ (embedded): SenseVoice.cpp — no Python dependency
Quick start
from funasr import AutoModel
model = AutoModel(model="iic/SenseVoiceSmall", vad_model="fsmn-vad")
result = model.generate(input=audio)
Feature Request
Owl is a great personal wearable AI that runs locally. Suggesting SenseVoice as an ASR option — its compact size and speed make it ideal for local/edge deployment.
Why SenseVoice for wearable AI?
Local deployment options
pip install funasrQuick start