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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()
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