Update app.py

app.py

@@ -11,9 +11,8 @@ pipe_translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ar-en")
 
 # Initialize text-to-speech models for Arabic and English
 # Arabic: text-to-speech
-synthesiser_arabic = pipeline("text-to-speech", model="MBZUAI/speecht5_tts_clartts_ar")
-embeddings_dataset_arabic = load_dataset("herwoww/arabic_xvector_embeddings", split="validation")
-speaker_embedding_arabic = torch.tensor(embeddings_dataset_arabic[105]["speaker_embeddings"]).unsqueeze(0)
+synthesiser_arabic = synthesiser_arabic = pipeline("text-to-speech", model="facebook/mms-tts-ara")
+
 
 # English: text-to-speech
 synthesiser_english = pipeline("text-to-speech", model="microsoft/speecht5_tts")
@@ -48,10 +47,9 @@ def generate_poem_english(text):
     clean_text = clean_text.replace("\\n", " ")  # Replace newlines with a space
     return clean_text
 
-# Text-to-speech conversion for Arabic
 def text_to_speech_arabic(text):
-    speech = synthesiser_arabic(text, forward_params={"speaker_embeddings": speaker_embedding_arabic})
-    audio_data = speech["audio"]
+    speech = synthesiser_arabic(text)
+    audio_data = speech["audio"][0]  # Flatten to 1D
     sampling_rate = speech["sampling_rate"]
     return (sampling_rate, audio_data)