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@@ -0,0 +1,54 @@
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+import gradio as gr
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+import speech_recognition as sr
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+
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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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+
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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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+
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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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+
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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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+
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+ input_hijack.update({"state": True, "value": [transcription, transcription]})
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+
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+ text_state += transcription + " "
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+ return text_state, text_state
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+
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+
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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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+
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+
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+def auto_transcribe(audio, audio_auto, text_state=""):
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+ if audio is None:
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+ return "", ""
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+ if audio_auto:
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+ return do_stt(audio, text_state)
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+ return "", ""
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+
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+
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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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+ audio_auto = gr.Checkbox(label="Auto-Transcribe", value=True)
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+ with gr.Row():
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+ audio = gr.Audio(source="microphone")
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+ audio.change(fn=auto_transcribe, inputs=[audio, audio_auto, tr_state], outputs=[output_transcription, tr_state])
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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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