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| import os | |
| import unicodedata | |
| from transformers import pipeline | |
| import gradio as gr | |
| # Set the Hugging Face token | |
| HF_TOKEN = "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" | |
| os.environ["HF_TOKEN"] = HF_TOKEN | |
| # Define the ASR function | |
| def asr(audio): | |
| asr = pipeline("automatic-speech-recognition", model="kingabzpro/wav2vec2-large-xls-r-300m-Urdu") | |
| prediction = asr(audio, chunk_length_s=30) | |
| return unicodedata.normalize("NFC", prediction[0]["text"]) | |
| # Define the Gradio interface | |
| title = "Urdu Automatic Speech Recognition" | |
| description = "This model performs automatic speech recognition for the Urdu language." | |
| input_audio = gr.inputs.Audio(source="microphone", type="numpy", label="Record your voice") | |
| output_text = gr.outputs.Textbox(label="Transcription") | |
| gr.Interface(fn=asr, inputs=input_audio, outputs=output_text, title=title, description=description).launch() | |
| # Ensure to replace "YOUR_HF_TOKEN" with your actual Hugging Face token. | |