#!/usr/bin/env python3
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# -*- encoding: utf-8 -*-
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# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
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# MIT License (https://opensource.org/licenses/MIT)
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from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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multilingual_wavs = [
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"https://www.modelscope.cn/api/v1/models/iic/speech_whisper-large_lid_multilingual_pytorch/repo?Revision=master&FilePath=examples/example_zh-CN.mp3",
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"https://www.modelscope.cn/api/v1/models/iic/speech_whisper-large_lid_multilingual_pytorch/repo?Revision=master&FilePath=examples/example_en.mp3",
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"https://www.modelscope.cn/api/v1/models/iic/speech_whisper-large_lid_multilingual_pytorch/repo?Revision=master&FilePath=examples/example_ja.mp3",
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"https://www.modelscope.cn/api/v1/models/iic/speech_whisper-large_lid_multilingual_pytorch/repo?Revision=master&FilePath=examples/example_ko.mp3",
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]
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inference_pipeline = pipeline(
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task=Tasks.auto_speech_recognition, model="iic/speech_whisper-large_lid_multilingual_pytorch"
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)
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for wav in multilingual_wavs:
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rec_result = inference_pipeline(input=wav, inference_clip_length=250)
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print(rec_result)
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