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| import gradio as gr | |
| from transformers import pipeline | |
| # from huggingsound import SpeechRecognitionModel | |
| from scipy.io.wavfile import write | |
| from huggingsound import SpeechRecognitionModel | |
| model = SpeechRecognitionModel("jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn") | |
| # audio_paths = ["/path/to/file.mp3", "/path/to/another_file.wav"] | |
| # transcriptions = model.transcribe(audio_paths) | |
| def func(input_audio): | |
| print(input_audio ) | |
| write('./audio.wav', input_audio[0], input_audio[1]) | |
| out_txt = model.transcribe(['./audio.wav']) | |
| return out_txt[0]['transcription'] | |
| inp =[gr.Audio(source='microphone')] | |
| out = [gr.Textbox()] | |
| demo = gr.Interface(func, | |
| # gr.Audio(source='microphone'), | |
| inputs = inp, | |
| outputs = out) | |
| # examples=examples) | |
| demo.launch() |