FunASR/examples/industrial_data_pretraining/seaco_paraformer/demo.py
2024-02-05 11:15:06 +08:00

45 lines
1.6 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
model = AutoModel(model="iic/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch",
model_revision="v2.0.4",
vad_model="damo/speech_fsmn_vad_zh-cn-16k-common-pytorch",
vad_model_revision="v2.0.4",
punc_model="damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch",
punc_model_revision="v2.0.4",
spk_model="damo/speech_campplus_sv_zh-cn_16k-common",
spk_model_revision="v2.0.2",
)
# example1
res = model.generate(input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav",
hotword='达摩院 魔搭',
# preset_spk_num=2,
# sentence_timestamp=True, # return sentence level information when spk_model is not given
)
print(res)
'''
# tensor or numpy as input
# example2
import torchaudio
import os
wav_file = os.path.join(model.model_path, "example/asr_example.wav")
input_tensor, sample_rate = torchaudio.load(wav_file)
input_tensor = input_tensor.mean(0)
res = model.generate(input=[input_tensor], batch_size_s=300, is_final=True)
# example3
import soundfile
wav_file = os.path.join(model.model_path, "example/asr_example.wav")
speech, sample_rate = soundfile.read(wav_file)
res = model.generate(input=[speech], batch_size_s=300, is_final=True)
'''