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| from transformers import pipeline | |
| import gradio as gr | |
| import time | |
| import unicodedata | |
| p = pipeline("automatic-speech-recognition",model="kingabzpro/wav2vec2-large-xls-r-300m-Urdu") | |
| def transcribe(audio, state=""): | |
| time.sleep(2) | |
| text = p(audio)["text"] | |
| state += unicodedata.normalize("NFC",text) + " " | |
| return state, state | |
| ################### Gradio Web APP ################################ | |
| title = "Real-Time Urdu ASR" | |
| description = """ | |
| <p> | |
| <center> | |
| This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. | |
| </center> | |
| </p> | |
| <center> | |
| <img src="https://huggingface.co/spaces/kingabzpro/real-time-Urdu-ASR/resolve/main/Images/cover.jpg" alt="logo" width="550"/> | |
| </center> | |
| """ | |
| article = "<p style='text-align: center'><a href='https://dagshub.com/kingabzpro/Urdu-ASR-SOTA' target='_blank'>Source Code on DagsHub</a></p><p style='text-align: center'><a href='https://huggingface.co/blog/fine-tune-xlsr-wav2vec2' target='_blank'>Fine-tuning XLS-R for Multi-Lingual ASR with 🤗 Transformers</a></p></center><center><img src='https://visitor-badge.glitch.me/badge?page_id=kingabzpro/real-time-Urdu-ASR' alt='visitor badge'></center></p>" | |
| gr.Interface( | |
| fn=transcribe, | |
| inputs=[ | |
| gr.Audio(source="microphone", type="filepath", streaming=True), | |
| "state" | |
| ], | |
| outputs=[ | |
| "textbox", | |
| "state" | |
| ], | |
| title=title, | |
| description=description, | |
| article=article, | |
| theme='EveryPizza/Cartoony-Gradio-Theme', | |
| live=True).launch() | |