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import gradio as gr
import torch
from transformers import SpeechT5ForTextToSpeech, SpeechT5Processor, SpeechT5HifiGan
import soundfile as sf
model = SpeechT5ForTextToSpeech.from_pretrained("Beehzod/speecht5_finetuned_uz_customData2")
processor = SpeechT5Processor.from_pretrained("Beehzod/speecht5_finetuned_uz_customData2")
vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan")
speaker_embeddings = torch.zeros((1, 512))
def text_to_speech(text):
inputs = processor(text=text, return_tensors="pt")
speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder)
output_path = "output.wav"
sf.write(output_path, speech.numpy(), 16000)
return output_path
interface = gr.Interface(
fn=text_to_speech,
inputs="text",
outputs="audio",
title="Uzbek Text-to-Speech Generator",
description="Enter Uzbek text and generate speech using the finetuned SpeechT5 model."
)
interface.launch()
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