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| from transformers import pipeline | |
| import gradio as gr | |
| modelName = "asrnepali" | |
| hfUser = "Hemg" | |
| def transcribe(audio, state=""): | |
| modelPath = hfUser + "/" + modelName | |
| p = pipeline("automatic-speech-recognition", model=modelPath) | |
| """ Speech to text function using pipeline""" | |
| text = p(audio)["text"] | |
| state += text + " " | |
| return state, state | |
| gr.Interface(fn=transcribe, | |
| inputs=[gr.inputs.Audio(source="upload", type="filepath", label="Record/ Drop audio"), "state"], | |
| outputs=["textbox", "state"], | |
| title="Automatic Speech Recognition test", | |
| description="Enable the recognition spoken language into text by computers.", | |
| theme="huggingface", | |
| live=True).launch() |