app.py

import streamlit as st
from speechbrain.pretrained import Tacotron2, HIFIGAN
from scipy.io.wavfile import write

# 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!")

# TTS function
def text_to_speech(text):
    # Generate mel spectrogram
    mel_output, mel_length, alignment = tacotron2.encode_text(text)
    
    # Decode mel spectrogram to waveform
    waveforms = hifi_gan.decode_batch(mel_output)
    
    # Convert waveform to numpy and normalize to int16 range
    waveform = waveforms.squeeze(1).cpu().numpy()
    waveform = waveform / max(abs(waveform))  # Normalize to range [-1, 1]
    waveform = (waveform * 32767).astype("int16")  # Scale to int16 range
    
    # Save waveform as audio file
    audio_path = "output.wav"
    write(audio_path, 22050, waveform)
    return audio_path

# 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():
        st.write("Generating speech...")
        try:
            audio_file = text_to_speech(text)
            st.audio(audio_file, format="audio/wav")
        except Exception as e:
            st.error(f"Error during TTS generation: {e}")
    else:
        st.warning("Please enter some text.")