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| import os | |
| from datasets import load_dataset, Audio | |
| from transformers import pipeline | |
| import gradio as gr | |
| ############### HF ########################### | |
| HF_TOKEN = os.getenv("HF_TOKEN") | |
| hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "Urdu-ASR-flags") | |
| ############## DVC ################################ | |
| Model = "Model" | |
| if os.path.isdir(".dvc"): | |
| print("Running DVC") | |
| # os.system("dvc config cache.type copy") | |
| # os.system("dvc config core.no_scm true") | |
| if os.system(f"dvc pull {Model} -r origin") != 0: | |
| exit("dvc pull failed") | |
| # os.system("rm -r .dvc") | |
| # .apt/usr/lib/dvc | |
| ############## Inference ############################## | |
| def asr(audio): | |
| asr = pipeline("automatic-speech-recognition", model=Model) | |
| prediction = asr(audio, chunk_length_s=5, stride_length_s=1) | |
| return prediction | |
| ################### Gradio Web APP ################################ | |
| title = "Urdu Automatic Speech Recognition" | |
| description = """ | |
| <p> | |
| <center> | |
| This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. | |
| <img src="https://huggingface.co/spaces/kingabzpro/Urdu-ASR-SOTA/blob/main/Images/cover.jpg" alt="logo" width="250"/> | |
| </center> | |
| </p> | |
| """ | |
| article = """<p style='text-align: center'> | |
| <a href='https://dagshub.com/kingabzpro/Urdu-ASR-SOTA' target='_blank'> | |
| Source Code on DagsHub</a> | |
| </center></p>""" | |
| examples = [["Sample/sample1.mp3"], ["Sample/sample2.mp3"], ["Sample/sample3.mp3"]] | |
| Input = gr.inputs.Audio( | |
| source="microphone", | |
| type="filepath", | |
| optional=True, | |
| label="Please Record Your Voice", | |
| ) | |
| Output = gr.outputs.Textbox(label="Urdu Script") | |
| def main(): | |
| iface = gr.Interface( | |
| asr, | |
| Input, | |
| Output, | |
| title=title, | |
| flagging_options=["incorrect", "worst", "ambiguous"], | |
| allow_flagging="manual", | |
| flagging_callback=hf_writer, | |
| description=description, | |
| article=article, | |
| examples=examples, | |
| theme="peach", | |
| ) | |
| iface.launch(enable_queue=True) | |
| # enable_queue=True,auth=("admin", "pass1234") | |
| if __name__ == "__main__": | |
| main() | |