Update app.py

app.py

@@ -25,7 +25,7 @@ speaker_embeddings = torch.tensor(embeddings_dataset[7306]["xvector"]).unsqueeze
 translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-ru", device=device)
 
 def translate(audio):
-    outputs = asr_pipe(audio, max_new_tokens=256, generate_kwargs={"task": "transcribe"})
+    outputs = asr_pipe(audio, max_new_tokens=256, generate_kwargs={"task": "translate"})
     translated_text = translator(outputs["text"])
     return translated_text[0]['translation_text']