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import gradio as gr
import time
from transformers import pipeline
def tts_inference(text, model_name):
model = {"reference": model_name}
pipe = pipeline("text-to-speech", model=model['reference'])
print('Processing...')
t = time.time()
output = pipe(text)
t = time.time() - t
print(f"Took {round(t)} seconds")
return (output["audio"], output["sampling_rate"])
# List of available TTS models
available_models = [
"microsoft/speecht5_tts",
"facebook/mms-tts-eng",
"suno/bark"
]
gr.Interface(
fn=tts_inference,
inputs=[
gr.Textbox(label="Enter text", placeholder="Type something to convert to speech..."),
gr.Dropdown(available_models, label="Select Model")
],
outputs=gr.Audio(type="numpy", label="Generated Speech"),
title="Hugging Face TTS Space",
description="Enter text and generate speech using Hugging Face's text-to-speech models."
).launch()
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