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import gradio as gr
from TTS.api import TTS
from bark import SAMPLE_RATE, generate_audio, preload_models
from scipy.io.wavfile import write as write_wav
from IPython.display import Audio
# download and load all models
preload_models()
def bark_try():
# generate audio from text
text_prompt = """
Hello, my name is Suno. And, uh — and I like pizza. [laughs]
But I also have other interests such as playing tic tac toe.
"""
audio_array = generate_audio(text_prompt)
# save audio to disk
write_wav("bark_generation.wav", SAMPLE_RATE, audio_array)
# play text in notebook
#Audio(audio_array, rate=SAMPLE_RATE)
return ("bark_generation.wav")
def try1():
model_name1 = TTS.list_models()
print (f"model1 Name: {model_name1}")
model_name = model_name1[0]
print (f"model2 Name: {model_name}")
# Init TTS
tts = TTS(model_name)
# Run TTS
# ❗ Since this model is multi-speaker and multi-lingual, we must set the target speaker and the language
# Text to speech with a numpy output
#wav = tts.tts("This is a test! This is also a test!!", speaker=tts.speakers[0], language=tts.languages[0])
# Text to speech to a file
tts.tts_to_file(text="Hello world!", speaker=tts.speakers[0], language=tts.languages[0], file_path="./output.wav")
out = "./output.wav"
return out
#def try2():
#tts = TTS(model_name="tts_models/multilingual/multi-dataset/your_tts", progress_bar=False, gpu=False)
#tts.tts_to_file("This is voice cloning.", speaker_wav="my/cloning/audio.wav", language="en", file_path="output.wav")
#tts.tts_to_file("C'est le clonage de la voix.", speaker_wav="my/cloning/audio.wav", language="fr", file_path="output.wav")
#tts.tts_to_file("Isso é clonagem de voz.", speaker_wav="my/cloning/audio.wav", language="pt", file_path="output.wav")
#out = "output.wav"
#return out
with gr.Blocks() as app:
out1 = gr.Audio()
btn1 = gr.Button()
btn2 = gr.Button()
btn1.click(bark_try,None,out1)
#btn2.click(try2,None,out1)
app.launch() |