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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
- multilingual_wavs = [
- "example_zh-CN.mp3",
- "example_en.mp3",
- "example_ja.mp3",
- "example_ko.mp3",
- ]
- model = AutoModel(model="iic/speech_whisper-large_lid_multilingual_pytorch", model_revision="v2.0.4")
- for wav_id in multilingual_wavs:
- wav_file = f"{model.model_path}/examples/{wav_id}"
- res = model.generate(input=wav_file, data_type="sound", inference_clip_length=250)
- print("detect sample {}: {}".format(wav_id, res))
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