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from scipy.io.wavfile import write as write_wav | |
from transformers import AutoProcessor, BarkModel | |
import gradio | |
processor = AutoProcessor.from_pretrained("suno/bark-small") | |
model = BarkModel.from_pretrained("suno/bark-small") | |
def generate_speech(text, voice_preset="v2/en_speaker_6"): | |
inputs = processor(text, voice_preset=voice_preset) | |
audio_array = model.generate(**inputs) | |
audio_array = audio_array.cpu().numpy().squeeze() | |
# save audio to disk, but first take the sample rate from the model config | |
sample_rate = model.generation_config.sample_rate | |
write_wav("bark_generation.wav", sample_rate, audio_array) | |
return "bark_generation.wav" | |
# generate_speech("Hello uh ... [clears throat], my dog is cute [laughter]") | |
iface = gradio.Interface(fn = generate_speech, | |
inputs = 'text', | |
outputs = 'audio', | |
title = 'Text to Speech' | |
) | |
iface.launch(share=True) | |