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| import torch | |
| import gradio as gr | |
| import pytube as pt | |
| from transformers import pipeline | |
| from huggingface_hub import model_info | |
| import time | |
| import unicodedata | |
| # from gradio.themes.utils.theme_dropdown import create_theme_dropdown | |
| MODEL_NAME = "SakshiRathi77/wav2vec2-large-xlsr-300m-hi-kagglex" | |
| lang = "hi" | |
| # my_theme = gr.Theme.from_hub('freddyaboulton/dracula_revamped') | |
| device = 0 if torch.cuda.is_available() else "cpu" | |
| pipe = pipeline( | |
| task="automatic-speech-recognition", | |
| model=MODEL_NAME, | |
| device=device, | |
| ) | |
| def transcribe(microphone, file_upload): | |
| warn_output = "" | |
| if (microphone is not None) and (file_upload is not None): | |
| warn_output = ( | |
| "WARNING: You've uploaded an audio file and used the microphone. " | |
| "The recorded file from the microphone will be used and the uploaded audio will be discarded.\n" | |
| ) | |
| elif (microphone is None) and (file_upload is None): | |
| return "ERROR: You have to either use the microphone or upload an audio file" | |
| file = microphone if microphone is not None else file_upload | |
| text = pipe(file)["text"] | |
| return warn_output + text | |
| def rt_transcribe(audio, state=""): | |
| time.sleep(2) | |
| text = pipe(audio)["text"] | |
| state += unicodedata.normalize("NFC",text) + " " | |
| return state, state | |
| demo = gr.Blocks() | |
| examples=[["examples/example1.mp3"], ["examples/example2.mp3"],["examples/example3.mp3"]] | |
| title =""" | |
| HindiSpeechPro: WAV2VEC-Powered ASR Interface | |
| """ | |
| description = """ | |
| <p> | |
| <center> | |
| Welcome to the HindiSpeechPro, a cutting-edge interface powered by a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. | |
| <img src="https://huggingface.co/spaces/SakshiRathi77/SakshiRathi77-Wav2Vec2-hi-kagglex/resolve/main/Images/main_image2.png" alt="logo" ;> | |
| </center> | |
| </p> | |
| """ | |
| # article = "<p style='text-align: center'><a href='https://github.com/SakshiRathi77/ASR' target='_blank'>Source Code on Github</a></p><p style='text-align: center'><a href='https://huggingface.co/blog/fine-tune-xlsr-wav2vec2' target='_blank'>Reference</a></p><p style='text-align: center'><a href='https://forms.gle/hjfc3F1P7m3weQVAA' target='_blank'><img src='https://e7.pngegg.com/pngimages/794/310/png-clipart-customer-review-feedback-user-service-others-miscellaneous-text-thumbnail.png' alt='Feedback Form' ;></a></p>" | |
| mf_transcribe = gr.Interface( | |
| fn=transcribe, | |
| inputs=[ | |
| gr.inputs.Audio(source="microphone", type="filepath"), | |
| gr.inputs.Audio(source="upload", type="filepath"), | |
| ], | |
| outputs="text", | |
| # theme="huggingface", | |
| title=title, | |
| description= description , | |
| allow_flagging="never", | |
| examples=examples, | |
| ) | |
| rt_transcribe = gr.Interface( | |
| fn=rt_transcribe, | |
| inputs=[ | |
| gr.Audio(source="microphone", type="filepath", streaming=True), | |
| "state" | |
| ], | |
| outputs=[ "textbox", | |
| "state"], | |
| # theme="huggingface", | |
| title=title, | |
| description= description , | |
| allow_flagging="never", | |
| live=True, | |
| ) | |
| with demo: | |
| gr.TabbedInterface([mf_transcribe, rt_transcribe], ["Transcribe Audio", "Transcribe Realtime Voice"]) | |
| demo.launch(share=True) | |