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import os | |
from transformers import BarkModel | |
from transformers import AutoProcessor | |
###### BARK | |
model_bark = BarkModel.from_pretrained("suno/bark") | |
processor_bark = AutoProcessor.from_pretrained("suno/bark") | |
#from mms import generate_audio_mms | |
from tts import synthesize, TTS_LANGUAGES | |
import torch | |
device = "cuda:0" if torch.cuda.is_available() else "cpu" | |
model_bark = model_bark.to(device) | |
def generate_audio_bark(input): | |
voice_preset = "v2/es_speaker_1" | |
inputs = processor_bark(input, voice_preset=voice_preset) | |
# generate speech | |
sampling_rate = model_bark.generation_config.sample_rate | |
speech_output = model_bark.generate(**inputs.to(device)) | |
return sampling_rate,speech_output[0].cpu().numpy() | |
import gradio as gr | |
with gr.Blocks() as demo: | |
with gr.Tab("MMS"): | |
with gr.Row(): | |
with gr.Column(): | |
textbox = gr.Textbox(label="Ingrese texto") | |
button = gr.Button("Hablar") | |
with gr.Column(): | |
audio_output = gr.Audio() | |
with gr.Tab("Bark"): | |
with gr.Row(): | |
with gr.Column(): | |
textbox2= gr.Textbox(label="Ingrese text") | |
button2 = gr.Button("Hablar") | |
with gr.Column(): | |
audio_output2 = gr.Audio() | |
button.click(synthesize,textbox,audio_output) | |
button2.click(generate_audio_bark,textbox2,audio_output2) | |
demo.launch() |