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| import gradio as gr | |
| from transformers import pipeline | |
| # Use the NCAIR Yoruba model | |
| # This might require a slightly larger Space (CPU Upgrade) or might run slowly on Free Tier | |
| transcriber = pipeline("automatic-speech-recognition", model="NCAIR1/Yoruba-ASR") | |
| def transcribe(audio): | |
| text = transcriber(audio)["text"] | |
| return text | |
| iface = gr.Interface( | |
| fn=transcribe, | |
| inputs=gr.Audio(type="filepath"), # Upload or Record audio | |
| outputs="text", | |
| title="Yoruba Speech Transcriber", | |
| description="Speak or upload Yoruba audio to transcribe it to text." | |
| ) | |
| iface.launch() |