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Simplest speech to text example
Browse files- .gitignore +1 -0
- app.py +28 -0
- packages.txt +1 -0
- requirements.txt +2 -0
.gitignore
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/venv
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app.py
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from transformers import pipeline, AutoFeatureExtractor, AutoTokenizer, Wav2Vec2ForCTC
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import gradio as gr
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import time
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model_id = 'comodoro/wav2vec2-xls-r-300m-cs-250'
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feature_extractor = AutoFeatureExtractor.from_pretrained(model_id)
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model = Wav2Vec2ForCTC.from_pretrained(model_id)
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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p = pipeline("automatic-speech-recognition", chunk_length_s=5, model=model,
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tokenizer=tokenizer, feature_extractor=feature_extractor)
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def transcribe(audio, state=""):
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time.sleep(2)
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text = p(audio)["text"]
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state += text + " "
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return state
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with gr.Blocks() as blocks:
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audio = gr.Audio(source="microphone", type="filepath",
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label='Pokud je to třeba, povolte mikrofon pro tuto stránku, \
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klikněte na Record from microphone, po dokončení nahrávání na Stop recording a poté na Rozpoznat')
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btn = gr.Button('Rozpoznat')
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output = gr.Textbox(show_label=False)
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btn.click(fn=transcribe, inputs=[audio,],
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outputs=[output,])
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blocks.launch(enable_queue=True, debug=True)
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packages.txt
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ffmpeg
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requirements.txt
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torch
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transformers
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