Create app.py

app.py

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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()