Update app.py

app.py

@@ -15,10 +15,10 @@ asr_pipe = pipeline("automatic-speech-recognition", model="openai/whisper-base",
 processor = SpeechT5Processor.from_pretrained("microsoft/speecht5_tts")
 
 # Using a different text-to-speech model (replace 'your_text_to_speech_model' with the model you want to use)
-model = SpeechT5ForTextToSpeech.from_pretrained("your_text_to_speech_model").to(device)
+model = SpeechT5ForTextToSpeech.from_pretrained("elizabetvaganova/speech-to-speech-translation-vaganova").to(device)
 
 # Using a different vocoder model (replace 'your_vocoder_model' with the model you want to use)
-vocoder = SpeechT5HifiGan.from_pretrained("your_vocoder_model").to(device)
+vocoder = SpeechT5HifiGan.from_pretrained("elizabetvaganova/speech-to-speech-translation-vaganova").to(device)
 
 embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
 speaker_embeddings = torch.tensor(embeddings_dataset[7306]["xvector"]).unsqueeze(0)