50 lines
1.3 KiB
Python
50 lines
1.3 KiB
Python
#!/usr/bin/env python3
|
|
# -*- encoding: utf-8 -*-
|
|
# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
|
|
# MIT License (https://opensource.org/licenses/MIT)
|
|
|
|
from funasr import AutoModel
|
|
|
|
wav_file = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/vad_example.wav"
|
|
|
|
model = AutoModel(model="iic/speech_fsmn_vad_zh-cn-16k-common-pytorch")
|
|
|
|
res = model.generate(input=wav_file)
|
|
print(res)
|
|
|
|
# [[beg1, end1], [beg2, end2], .., [begN, endN]]
|
|
# beg/end: ms
|
|
|
|
|
|
import soundfile
|
|
import os
|
|
|
|
wav_file = os.path.join(model.model_path, "example/vad_example.wav")
|
|
speech, sample_rate = soundfile.read(wav_file)
|
|
|
|
chunk_size = 200 # ms
|
|
chunk_stride = int(chunk_size * sample_rate / 1000)
|
|
|
|
cache = {}
|
|
|
|
total_chunk_num = int(len((speech) - 1) / chunk_stride + 1)
|
|
for i in range(total_chunk_num):
|
|
speech_chunk = speech[i * chunk_stride : (i + 1) * chunk_stride]
|
|
is_final = i == total_chunk_num - 1
|
|
res = model.generate(
|
|
input=speech_chunk,
|
|
cache=cache,
|
|
is_final=is_final,
|
|
chunk_size=chunk_size,
|
|
disable_pbar=True,
|
|
)
|
|
# print(res)
|
|
if len(res[0]["value"]):
|
|
print(res)
|
|
|
|
|
|
# 1. [[beg1, end1], [beg2, end2], .., [begN, endN]]; [[beg, end]]; [[beg1, end1], [beg2, end2]]
|
|
# 2. [[beg, -1]]
|
|
# 3. [[-1, end]]
|
|
# beg/end: ms
|