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import gradio as gr |
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from transformers import pipeline |
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import numpy as np |
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transcriber = pipeline("automatic-speech-recognition", model="bartelds/gos-gpu6-cp1_adp0_192m_no_test_1e-5_cp-12000") |
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def transcribe(audio): |
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sr, y = audio |
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y = y.astype(np.float32) |
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y /= np.max(np.abs(y)) |
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return transcriber({"sampling_rate": sr, "raw": y})["text"] |
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demo = gr.Interface( |
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transcribe, |
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gr.Audio(source="upload"), |
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"text", |
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title="Speech-to-text for Gronings", |
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description="Upload an audio file (in 16 kHz) with Gronings speech to obtain its transcription. Example files are in our [gos-demo](https://huggingface.co/datasets/bartelds/gos-demo) dataset." |
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) |
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demo.launch() |
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