FireRedVAD for fasr (bundled fireredvad inference)
Project description
fasr-vad-firered
基于 FireRedVAD 的语音活动检测模型插件,为 fasr 提供非流式 VAD 能力。
安装
pip install fasr-vad-firered
注册模型
| 注册名 | 类 | 默认 checkpoint | 说明 |
|---|---|---|---|
firered |
FireRedForVAD |
xukaituo/FireRedVAD |
非流式 VAD,基于神经网络的语音段检测 |
模型权重默认从 ModelScope 自动下载。权重目录需包含 cmvn.ark 和 model.pth.tar。
使用方式
在流水线中使用
from fasr import AudioPipeline
pipeline = (
AudioPipeline()
.add_pipe("detector", model="firered")
.add_pipe("recognizer", model="firered_aed", checkpoint_dir="/path/to/asr-ckpt")
.add_pipe("sentencizer", model="ct_transformer")
)
单独使用模型
from fasr.config import registry
from fasr.data import Waveform
model = registry.vad_models.get("firered")()
model.from_checkpoint(use_gpu=True, speech_threshold=0.4)
waveform = Waveform.from_file("example.wav")
segments = model.detect(waveform)
for seg in segments:
print(f"{seg.start_ms}ms - {seg.end_ms}ms")
from_checkpoint 参数
| 参数 | 类型 | 默认值 | 说明 |
|---|---|---|---|
checkpoint_dir |
str | Path | None |
None(自动下载) |
模型权重目录,需含 cmvn.ark 和 model.pth.tar |
use_gpu |
bool |
False |
是否使用 GPU 推理 |
speech_threshold |
float |
0.4 |
语音判定阈值,越小越敏感 |
依赖
fasrtorch >= 2.0.0soundfile >= 0.12.0kaldiio >= 2.18.0、kaldi-native-fbank >= 1.19.0- Python 3.10–3.12
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