Update app.py

app.py

@@ -11,7 +11,7 @@ device = "cuda:0" if torch.cuda.is_available() else "cpu"
 asr_pipe = pipeline("automatic-speech-recognition", model="openai/whisper-base", device=device)
 
 # load text-to-speech checkpoint and speaker embeddings
-model_id = "burraco135/speech-to-speech-translation"  # update with your model id
+model_id = "burraco135/speecht5_finetuned_voxpopuli_it"  # update with your model id
 # pipe = pipeline("automatic-speech-recognition", model=model_id)
 model = SpeechT5ForTextToSpeech.from_pretrained(model_id)
 processor = SpeechT5Processor.from_pretrained(model_id)
@@ -57,7 +57,7 @@ def speech_to_speech_translation(audio):
 
 title = "Cascaded STST"
 description = """
-Demo for cascaded speech-to-speech translation (STST), mapping from source speech in any language to target speech in German. Demo uses OpenAI's [Whisper Base](https://huggingface.co/openai/whisper-base) model for speech translation, and [burraco135/speech-to-speech-translation](https://huggingface.co/burraco135/speecht5_finetuned_voxpopuli_it) checkpoint for text-to-speech, which is based on Microsoft's
+Demo for cascaded speech-to-speech translation (STST), mapping from source speech in any language to target speech in German. Demo uses OpenAI's [Whisper Base](https://huggingface.co/openai/whisper-base) model for speech translation, and [burraco135/speecht5_finetuned_voxpopuli_it](https://huggingface.co/burraco135/speecht5_finetuned_voxpopuli_it) checkpoint for text-to-speech, which is based on Microsoft's
 [SpeechT5 TTS](https://huggingface.co/microsoft/speecht5_tts) model for text-to-speech, fine-tuned in Italian Audio dataset:
 ![Cascaded STST](https://huggingface.co/datasets/huggingface-course/audio-course-images/resolve/main/s2st_cascaded.png "Diagram of cascaded speech to speech translation")
 """