Create app.py

app.py

@@ -2,16 +2,19 @@ import streamlit as st
 from speechbrain.pretrained import Tacotron2, HIFIGAN
 from scipy.io.wavfile import write
 
-# Load the TTS and Vocoder models
+# Load the TTS and vocoder models
 @st.cache_resource
 def load_models():
     tacotron2 = Tacotron2.from_hparams(source="speechbrain/tts-tacotron2-ljspeech", savedir="tmpdir_tts")
     hifi_gan = HIFIGAN.from_hparams(source="speechbrain/tts-hifigan-ljspeech", savedir="tmpdir_vocoder")
     return tacotron2, hifi_gan
 
+# Load models
+st.write("Loading models... Please wait ⏳")
 tacotron2, hifi_gan = load_models()
+st.success("Models loaded successfully!")
 
-# Text-to-Speech function
+# TTS function
 def text_to_speech(text):
     mel_output, mel_length, alignment = tacotron2.encode_text(text)
     waveforms, _, _ = hifi_gan.decode_batch(mel_output)
@@ -19,11 +22,9 @@ def text_to_speech(text):
     write(audio_path, 22050, waveforms.squeeze(1).cpu().numpy())
     return audio_path
 
-# Streamlit App UI
-st.title("Text-to-Speech Chatbot")
-
-# Input text box
-text = st.text_input("Enter text to convert to speech:", "")
+# Streamlit UI
+st.title("🗣️ Text-to-Speech App")
+text = st.text_input("Enter text to convert to speech:")
 
 if st.button("Generate Speech"):
     if text.strip():
@@ -32,5 +33,3 @@ if st.button("Generate Speech"):
         st.audio(audio_file, format="audio/wav")
     else:
         st.warning("Please enter some text.")
-
-st.write("Powered by SpeechBrain and Streamlit.")