Update app.py

Changed the vocoder back to microsoft/speecht5_hifigan
and max_new_tokens to 128 to prevent runtime error

app.py

@@ -16,14 +16,14 @@ asr_pipe = pipeline("automatic-speech-recognition", model="openai/whisper-base",
 processor = SpeechT5Processor.from_pretrained("RajkNakka/speecht5_finetuned_voxpopuli_nl")
 
 model = SpeechT5ForTextToSpeech.from_pretrained("RajkNakka/speecht5_finetuned_voxpopuli_nl").to(device)
-vocoder = SpeechT5HifiGan.from_pretrained("RajkNakka/speecht5_finetuned_voxpopuli_nl").to(device)
+vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan").to(device)
 
 embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
 speaker_embeddings = torch.tensor(embeddings_dataset[7306]["xvector"]).unsqueeze(0)
 
 
 def translate(audio):
-    outputs = asr_pipe(audio, max_new_tokens=256, generate_kwargs={"task": "transcribe", "language": "nl"})
+    outputs = asr_pipe(audio, max_new_tokens=128, generate_kwargs={"task": "transcribe", "language": "nl"})
     return outputs["text"]