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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")
| 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))
|
|
