test4 / app.py
GuillermoPuma
pipe
b130f29
from huggingsound import SpeechRecognitionModel
from transformers import pipeline
import gradio as gr
#model = SpeechRecognitionModel("patrickvonplaten/wav2vec2-large-xlsr-53-spanish-with-lm")
pipe = pipeline("automatic-speech-recognition", "patrickvonplaten/wav2vec2-large-xlsr-53-spanish-with-lm")
def transcribe(audio, state=""):
#transcriptions_es = model.transcribe([audio])[0]
transcriptions_es = pipe(audio)["text"]
# Algoritmo here
recomendacion = "definir variable"
return transcriptions_es, recomendacion
inputs = gr.inputs.Audio(label="Dar click para escuchar tu voz", type="filepath", source="microphone")
output1 = gr.outputs.Textbox(label="Asi se ve tu c贸digo")
output2 = gr.outputs.Textbox(label="Tal vez quisiste decir:")
title = "Expresate con voz"
description = "Aplicaci贸n que ayuda a programar a traves de tu voz"
examples = ['definir funci贸n', 'definir variable', 'definir clase']
article = "<a style='color:#eb9f59;' href = 'https://github.com/gandres-dev/Hackaton-Common-Voice'> Repositorio de la app"
demo = gr.Interface(fn=transcribe, inputs=inputs, outputs=[output1,output2],
title=title, description=description, article=article,
allow_flagging="never", theme="darkpeach", examples=examples,
#live=True
)
if __name__ == "__main__":
demo.launch()