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import gradio as gr | |
from transformers import pipeline | |
trans = pipeline("automatic-speech-recognition", model = "facebook/wav2vec2-large-xlsr-53-spanish") | |
clasificador = pipeline("text-classification", model = "pysentimiento/robertuito-sentiment-analysis") | |
def audio_a_text(audio): | |
text = trans(audio)["text"] | |
return text | |
def texto_a_sentimiento(text): | |
return clasificador(text)[0]["label"] | |
demo = gr.Blocks() | |
with demo: | |
gr.Markdown("demo de sentimientos leidos") | |
audio = gr.Audio(source="microphone", type="filepath") | |
texto = gr.Textbox() | |
b1 = gr.Button("Dictado") | |
b1.click(audio_a_text, inputs=audio, outputs=texto) | |
label = gr.Label() | |
b2 = gr.Button("ΒΏGusto?") | |
b2.click(texto_a_sentimiento, inputs=texto, outputs=label) | |
demo.launch(share=True) | |