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