#!/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/LCB-NET",
|
model_revision="v1.0.0")
|
|
|
# example1
|
res = model.generate(input=("https://www.modelscope.cn/api/v1/models/iic/LCB-NET/repo?Revision=master&FilePath=example/asr_example.wav","https://www.modelscope.cn/api/v1/models/iic/LCB-NET/repo?Revision=master&FilePath=example/ocr.txt"),data_type=("sound", "text"))
|
|
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)
|
'''
|
