app.py

import streamlit as st
from transformers import SpeechT5Processor, SpeechT5ForTextToSpeech, SpeechT5HifiGan
from datasets import load_dataset
import torch
import soundfile as sf

st.title('Dummy Text To Speech')
text = st.text_input(
    label="Enter the text you want to convert to speech",
	value = "Hi, Welcome to theserverfault.com"
)

def generate_speech():
    processor = SpeechT5Processor.from_pretrained("microsoft/speecht5_tts")
    model = SpeechT5ForTextToSpeech.from_pretrained("microsoft/speecht5_tts")
    vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan")
    inputs = processor(text=text, return_tensors="pt")

    embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
    speaker_embeddings = torch.tensor(embeddings_dataset[7306]["xvector"]).unsqueeze(0)

    speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder)

    sf.write("speech.wav", speech.numpy(), samplerate=16000)

if st.button("Generate"):
      generate_speech()
      audio_file = open("speech.wav", 'rb')
      audio_bytes = audio_file.read()
      st.audio(audio_bytes, format="audio/wav")