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| import streamlit as st | |
| from transformers import pipeline | |
| from gtts import gTTS | |
| from io import BytesIO | |
| import base64 | |
| # Define a function to generate text-to-speech audio | |
| def generate_tts(text, voice_type, language): | |
| # Hugging Face pipeline for text-to-speech in English | |
| if language == "English": | |
| model_id = "facebook/fastspeech2-en-ljspeech" | |
| tts_pipeline = pipeline("text-to-speech", model=model_id) | |
| audio_data = tts_pipeline(text, return_tensors=True).audio["array"] | |
| return audio_data | |
| # Google Text-to-Speech (gTTS) for Urdu | |
| elif language == "Urdu": | |
| tts = gTTS(text=text, lang="ur") | |
| mp3_fp = BytesIO() | |
| tts.write_to_fp(mp3_fp) | |
| mp3_fp.seek(0) | |
| return mp3_fp.read() | |
| # Configure Streamlit app | |
| st.title("Multilingual Text-to-Speech Application") | |
| st.write("Generate speech from text in American English and Urdu with different voice styles.") | |
| # Input fields for text and options | |
| text = st.text_area("Enter your text:", "Hello, welcome to the Text-to-Speech app!") | |
| voice_type = st.selectbox( | |
| "Select voice style:", ["Adult", "Child", "Cartoon"] | |
| ) | |
| language = st.selectbox("Select language:", ["English", "Urdu"]) | |
| if st.button("Generate Audio"): | |
| with st.spinner("Generating audio..."): | |
| try: | |
| audio_data = generate_tts(text, voice_type, language) | |
| if language == "English": | |
| # Provide the audio as a downloadable file | |
| st.audio(audio_data, format="audio/wav") | |
| elif language == "Urdu": | |
| b64 = base64.b64encode(audio_data).decode() | |
| href = f'<a href="data:audio/mpeg;base64,{b64}" download="output.mp3">Download Urdu Audio</a>' | |
| st.markdown(href, unsafe_allow_html=True) | |
| except Exception as e: | |
| st.error(f"Error: {e}") | |
| st.caption("Powered by Hugging Face Transformers and Google TTS") | |