Create app.py
Browse files
app.py
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import gradio as gr
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from transformers import pipeline
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pipe = pipeline("automatic-speech-recognition", "facebook/wav2vec2-base-960h")
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dictionary = {' ': '/',
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"'": '.----.',
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'0': '-----',
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'1': '.----',
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'2': '..---',
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'3': '...--',
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'4': '....-',
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'5': '.....',
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'6': '-....',
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'7': '--...',
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'8': '---..',
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'9': '----.',
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'?': '..--..',
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'A': '.-',
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'B': '-...',
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'C': '-.-.',
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'D': '-..',
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'E': '.',
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'F': '..-.',
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'G': '--.',
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'H': '....',
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'I': '..',
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'J': '.---',
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'K': '-.-',
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'L': '.-..',
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'M': '--',
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'N': '-.',
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'O': '---',
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'P': '.--.',
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'Q': '--.-',
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'R': '.-.',
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'S': '...',
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'T': '-',
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'U': '..-',
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'V': '...-',
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'W': '.--',
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'X': '-..-',
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'Y': '-.--',
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'Z': '--..',
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}
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def asr(speech):
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transcript = pipe(speech)['text']
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morseCode = ""
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for character in transcript:
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morseCode += dictionary[character] + " "
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return morseCode
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gr.Interface(fn=asr,
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inputs = gr.inputs.Audio(source="upload", type="filepath", label="Upload your audio file here"),
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outputs = gr.outputs.Textbox(type="str",label="Output Text"),
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).launch()
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