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45 lines
1.4 KiB
Python
45 lines
1.4 KiB
Python
import gradio as gr
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import speech_recognition as sr
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input_hijack = {
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'state': False,
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'value': ["", ""]
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}
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def do_stt(audio, text_state=""):
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transcription = ""
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r = sr.Recognizer()
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# Convert to AudioData
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audio_data = sr.AudioData(sample_rate=audio[0], frame_data=audio[1], sample_width=4)
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try:
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transcription = r.recognize_whisper(audio_data, language="english", model="base.en")
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except sr.UnknownValueError:
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print("Whisper could not understand audio")
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except sr.RequestError as e:
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print("Could not request results from Whisper", e)
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input_hijack.update({"state": True, "value": [transcription, transcription]})
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text_state += transcription + " "
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return text_state, text_state
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def update_hijack(val):
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input_hijack.update({"state": True, "value": [val, val]})
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return val
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def ui():
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tr_state = gr.State(value="")
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output_transcription = gr.Textbox(label="STT-Input",
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placeholder="Speech Preview. Click \"Generate\" to send",
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interactive=True)
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output_transcription.change(fn=update_hijack, inputs=[output_transcription], outputs=[tr_state])
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with gr.Row():
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audio = gr.Audio(source="microphone")
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transcribe_button = gr.Button(value="Transcribe")
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transcribe_button.click(do_stt, inputs=[audio, tr_state], outputs=[output_transcription, tr_state])
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