Update app.py

app.py

@@ -2,7 +2,7 @@ import torch
 from transformers import pipeline
 from datasets import load_dataset
 from transformers import AutoModel
-from transformers import SpeechT5Processor, Speech2Text2Speech, SpeechT5HifiGan
+from transformers import Speech2Text2Speech, SpeechT5HifiGan
 import numpy as np
 import gradio as gr
 
@@ -22,7 +22,7 @@ vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan")
 
 # Cargar los datos de embeddings del hablante
 embeddings_dataset = load_dataset("ovieyra21/mabama-v5", split="train")
-speaker_embeddings = torch.tensor(embeddings_dataset[0]["speaker_embedding"]).unsqueeze(0)
+speaker_embeddings = torch.tensor(embeddings_dataset[7306]["xvector"]).unsqueeze(0)
 
 # Función para sintetizar el habla
 def synthesise(text):