23 lines
1.1 KiB
Python
23 lines
1.1 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 modelscope.pipelines import pipeline
|
||
|
|
from modelscope.utils.constant import Tasks
|
||
|
|
|
||
|
|
multilingual_wavs = [
|
||
|
|
"https://www.modelscope.cn/api/v1/models/iic/speech_whisper-large_lid_multilingual_pytorch/repo?Revision=master&FilePath=examples/example_zh-CN.mp3",
|
||
|
|
"https://www.modelscope.cn/api/v1/models/iic/speech_whisper-large_lid_multilingual_pytorch/repo?Revision=master&FilePath=examples/example_en.mp3",
|
||
|
|
"https://www.modelscope.cn/api/v1/models/iic/speech_whisper-large_lid_multilingual_pytorch/repo?Revision=master&FilePath=examples/example_ja.mp3",
|
||
|
|
"https://www.modelscope.cn/api/v1/models/iic/speech_whisper-large_lid_multilingual_pytorch/repo?Revision=master&FilePath=examples/example_ko.mp3",
|
||
|
|
]
|
||
|
|
|
||
|
|
inference_pipeline = pipeline(
|
||
|
|
task=Tasks.auto_speech_recognition, model="iic/speech_whisper-large_lid_multilingual_pytorch"
|
||
|
|
)
|
||
|
|
|
||
|
|
for wav in multilingual_wavs:
|
||
|
|
rec_result = inference_pipeline(input=wav, inference_clip_length=250)
|
||
|
|
print(rec_result)
|