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# from speechbrain.inference.ASR import EncoderASR | |
# import gradio as gr | |
# model = EncoderASR.from_hparams("speechbrain/asr-wav2vec2-dvoice-wolof") | |
# def transcribe(audio): | |
# return model.transcribe_file(audio.name) | |
# demo = gr.Interface(fn=transcribe, inputs="file", outputs="text", | |
# title="Transcription automatique du wolof", | |
# description="Ce modèle transcrit un fichier audio en wolof en texte en utilisant l'alphabet latin.", | |
# input_label="Audio en wolof", | |
# output_label="Transcription alphabet latin" | |
# ) | |
# demo.launch() | |
from speechbrain.inference.ASR import EncoderASR | |
import gradio as gr | |
model = EncoderASR.from_hparams("speechbrain/asr-wav2vec2-dvoice-wolof") | |
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(sources=["microphone"]), | |
"text", | |
) | |
demo.launch() | |