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| import streamlit as st | |
| from transformers import pipeline, SpeechT5Processor, SpeechT5ForTextToSpeech, SpeechT5HifiGan | |
| import torch | |
| from transformers import TextToSpeechPipeline | |
| from datasets import load_dataset | |
| import io | |
| # Initialize translation models | |
| translator_urdu = pipeline("translation_en_to_ur", model="Helsinki-NLP/opus-mt-en-ur") | |
| translator_hindi = pipeline("translation_en_to_hi", model="Helsinki-NLP/opus-mt-en-hi") | |
| # Initialize TTS model | |
| processor = SpeechT5Processor.from_pretrained("microsoft/speecht5_tts") | |
| tts_model = SpeechT5ForTextToSpeech.from_pretrained("microsoft/speecht5_tts") | |
| vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan") | |
| xvectors = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation") | |
| # Function to translate text | |
| def translate_text(text, target_lang): | |
| if target_lang == "Urdu": | |
| translated = translator_urdu(text) | |
| elif target_lang == "Hindi": | |
| translated = translator_hindi(text) | |
| else: | |
| return None, "Error: Target language not supported." | |
| return translated[0]['translation_text'], None | |
| # Function to synthesize speech | |
| def synthesize_speech(text, target_lang): | |
| if target_lang not in ["Urdu", "Hindi"]: | |
| return None, "Error: TTS model not available for the selected language." | |
| inputs = processor(text, return_tensors="pt") | |
| speaker_embedding = torch.tensor(xvectors[0]["xvector"]).unsqueeze(0) | |
| speech = tts_model.generate_speech(inputs["input_ids"], speaker_embedding, vocoder=vocoder) | |
| # Convert the speech to an in-memory WAV file using io.BytesIO | |
| audio_io = io.BytesIO() | |
| audio_io.write(speech.numpy().tobytes()) | |
| audio_io.seek(0) | |
| return audio_io, None | |
| # Streamlit UI | |
| st.title("Language Translator") | |
| # Text input | |
| text_to_translate = st.text_input("Enter text in English", value="", key="input_text") | |
| # Language selection | |
| target_language = st.selectbox("Select Target Language", ["Urdu", "Hindi"]) | |
| if st.button("Translate"): | |
| # Clear previous input | |
| st.session_state.input_text = "" | |
| # Translation | |
| translated_text, error = translate_text(text_to_translate, target_language) | |
| if error: | |
| st.error(error) | |
| else: | |
| st.write(f"Translated text ({target_language}): {translated_text}") | |
| # Text-to-Speech | |
| audio_file, tts_error = synthesize_speech(translated_text, target_language) | |
| if tts_error: | |
| st.error(tts_error) | |
| else: | |
| st.audio(audio_file, format='audio/wav') | |