| |
|
|
| import gradio as gr |
| from transformers import pipeline |
| import numpy as np |
|
|
| transcriber = pipeline("automatic-speech-recognition", model="bartelds/gos-gpu6-cp1_adp0_192m_no_test_1e-5_cp-12000") |
|
|
| def transcribe(audio): |
| sr, y = audio |
| y = y.astype(np.float32) |
| y /= np.max(np.abs(y)) |
|
|
| return transcriber({"sampling_rate": sr, "raw": y})["text"] |
|
|
|
|
| demo = gr.Interface( |
| transcribe, |
| gr.Audio(source="upload"), |
| "text", |
| title="Speech-to-text for Gronings", |
| 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." |
| ) |
|
|
| demo.launch() |
|
|
