---
license: apache-2.0
base_model: FireRedTeam/FireRedVAD
pipeline_tag: voice-activity-detection
tags:
- voice-activity-detection
- vad
- dfsmn
- audio
- speech
- safetensors
- svod
---

# FireRedVAD — safetensors for Svod

The voice-activity-detection checkpoints of
[FireRedVAD](https://github.com/FireRedTeam/FireRedVAD)
([FireRedASR2S technical report, arXiv:2603.10420](https://arxiv.org/abs/2603.10420)) —
both the non-streaming model and the causal `Stream-VAD` model — converted
from the original `model.pth.tar` + `cmvn.ark` to single safetensors files for
the [Svod](https://github.com/npatsakula/svod) inference runtime. Weights are
unmodified f32 — only renamed, reshaped, and bundled with the CMVN statistics.

FireRedVAD is a feed-forward DFSMN (no recurrence): 8 FSMN layers with
depthwise temporal filters, operating on 80-bin kaldi log-mel fbank at 16 kHz
(25 ms window / 10 ms hop). It detects speech in 100+ languages; upstream
reports 97.57 F1 on FLEURS-VAD-102. The non-streaming model (588k params) has
lookback + lookahead filters; the streaming model (568k params) is causal-only
(`N2 = 0`) and carries a 19-frame conv cache per FSMN layer between chunks.

## Files

| file | contents |
|---|---|
| `firered_vad.safetensors` | non-streaming: 45 model tensors + `cmvn_means`/`cmvn_istd` `[80]` (global CMVN derived from `cmvn.ark`: variance floored at 1e-20, inverse std precomputed) |
| `golden.safetensors` | non-streaming parity reference for `assets/hello_zh.wav`: `samples` (16 kHz mono, `[-1, 1]` f32), `feat` (pre-CMVN `kaldi-native-fbank` output `[230, 80]`), `probs` (PyTorch `DetectModel` output `[230]`) |
| `firered_vad_stream.safetensors` | streaming (`Stream-VAD`): 37 model tensors (no lookahead filters) + the CMVN pair |
| `golden_stream.safetensors` | streaming parity reference, same wav: `samples`, `feat`, `probs` (cache-threaded chunkwise reference forward), `probs_full` (one whole-sequence causal forward), `chunk_frames` (the chunk size used, 16) |

## Architecture / config

Non-streaming: `idim=80, R=8, M=1, H=256, P=128, N1=20, S1=1, N2=20, S2=1,
odim=1`; streaming: identical except `N2=0` (no lookahead — strictly causal).
Both read from the checkpoints' embedded args.

Tensor schema: `fc1.{weight,bias}` (80→256), `fc2.{weight,bias}` (256→128),
`fsmn1.{lookback,lookahead}.weight` `[128, 1, 1, 20]`,
`blocks.{0..6}.{fc1.weight,fc1.bias,fc2.weight,lookback.weight,lookahead.weight}`,
`dnn.{weight,bias}` (128→256), `out.{weight,bias}` (256→1),
`cmvn_means`/`cmvn_istd` `[80]`. FSMN filters are reshaped from PyTorch's
`[P, 1, 20]` to `[P, 1, 1, 20]` for 2-D depthwise convolution. The streaming
file has no `*.lookahead.weight` keys.

## License & citation

Apache-2.0, matching the upstream
[FireRedVAD](https://github.com/FireRedTeam/FireRedVAD) release by Xiaohongshu.

```bibtex
@article{xu2026fireredasr2s,
  title={FireRedASR2S: A State-of-the-Art Industrial-Grade All-in-One Automatic Speech Recognition System},
  author={Xu, Kaituo and Jia, Yan and Huang, Kai and Chen, Junjie and Li, Wenpeng and Liu, Kun and Xie, Feng-Long and Tang, Xu and Hu, Yao},
  journal={arXiv preprint arXiv:2603.10420},
  year={2026}
}
```