Create app.py

app.py

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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")