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- #!/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
- chunk_size = [5, 10, 5] #[0, 10, 5] 600ms, [0, 8, 4] 480ms
- encoder_chunk_look_back = 0 #number of chunks to lookback for encoder self-attention
- decoder_chunk_look_back = 0 #number of encoder chunks to lookback for decoder cross-attention
- model = AutoModel(model="/Users/zhifu/Downloads/modelscope_models/speech_SCAMA_asr-zh-cn-16k-common-vocab8358-streaming", model_revision="v2.0.4")
- cache = {}
- res = model.generate(input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav",
- chunk_size=chunk_size,
- encoder_chunk_look_back=encoder_chunk_look_back,
- decoder_chunk_look_back=decoder_chunk_look_back,
- )
- print(res)
- import soundfile
- import os
- wav_file = os.path.join(model.model_path, "example/asr_example.wav")
- speech, sample_rate = soundfile.read(wav_file)
- chunk_stride = chunk_size[1] * 960 # 600ms、480ms
- 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,
- encoder_chunk_look_back=encoder_chunk_look_back,
- decoder_chunk_look_back=decoder_chunk_look_back,
- )
- print(res)
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