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import gradio as gr
import numpy as np
from kittentts import KittenTTS
print("Loading KittenTTS model...")
try:
tts_model = KittenTTS("KittenML/kitten-tts-nano-0.1")
print("Model loaded successfully.")
except Exception as e:
print(f"Error loading model: {e}")
exit()
AVAILABLE_VOICES = tts_model.available_voices
DEFAULT_VOICE = "expr-voice-5-m" if "expr-voice-5-m" in AVAILABLE_VOICES else AVAILABLE_VOICES[0]
def synthesize_speech(text, voice, speed):
"""
Generates audio using the selected text, voice, and speed.
"""
if not text.strip():
return (24000, np.zeros(0, dtype=np.int16))
audio_data = tts_model.generate(text, voice=voice, speed=speed)
return (24000, audio_data)
with gr.Blocks(theme=gr.themes.Soft()) as demo:
gr.Markdown(
"""
# 🐱 KittenTTS UI
A user-friendly interface for the KittenTTS text-to-speech model.
Select a voice, adjust the speed, and type your text to generate audio.
"""
)
with gr.Row():
with gr.Column(scale=3):
text_input = gr.Textbox(
lines=5,
label="Input Text",
placeholder="Type something here..."
)
with gr.Column(scale=1):
voice_dropdown = gr.Dropdown(
choices=AVAILABLE_VOICES,
value=DEFAULT_VOICE,
label="Voice Selection"
)
speed_slider = gr.Slider(
minimum=0.5,
maximum=2.0,
step=0.05,
value=1.0,
label="Speech Speed"
)
generate_button = gr.Button("Generate Audio", variant="primary")
audio_output = gr.Audio(label="Generated Speech", autoplay=True)
gr.Examples(
examples=[
["This is an example of a female voice.", "expr-voice-4-f", 1.0],
["This is an example of a male voice, speaking a bit faster.", "expr-voice-3-m", 1.25],
["The speed can also be slowed down for clarity.", "expr-voice-5-f", 0.8],
],
inputs=[text_input, voice_dropdown, speed_slider]
)
generate_button.click(
fn=synthesize_speech,
inputs=[text_input, voice_dropdown, speed_slider],
outputs=audio_output
)
demo.queue().launch() |