| import os |
| os.environ["TRANSFORMERS_NO_TF"] = "1" |
|
|
| from transformers import pipeline |
| import gradio as gr |
|
|
| |
| pipe = pipeline( |
| task="automatic-speech-recognition", |
| model="Devion333/wav2vec2-xls-r-300m-dv" |
| ) |
|
|
| def transcribe(audio): |
| return pipe(audio)["text"] |
|
|
| demo = gr.Interface( |
| fn=transcribe, |
| inputs=gr.Audio(sources=["microphone", "upload"], type="filepath"), |
| outputs="text", |
| title="Wav2Vec2 ASR Demo", |
| description="Realtime demo for English speech recognition using Devion333/wav2vec2-xls-r-300m-dv." |
| ) |
|
|
| if __name__ == "__main__": |
| demo.launch() |
|
|