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import gradio as gr | |
from TTS.api import TTS | |
# List available 🐸TTS models and choose the first one | |
model_name = TTS.list_models()[0] | |
# Init TTS | |
tts = TTS(model_name) | |
def text_to_speech(text: str, speaker_wav, language: str): | |
tts.tts_to_file(text, speaker_wav=speaker_wav, language=language, file_path="output.wav") | |
# tts.tts_to_file(text=text, speaker=tts.speakers[0], language=language, file_path="output.wav") | |
return 'output.wav' | |
inputs = [gr.Textbox(label="Input", value="Personalized learning platform for students with learning differences: You could develop an AI-powered platform that uses adaptive learning algorithms to provide personalized learning experiences for students with learning differences such as dyslexia or ADHD. As a front-end developer, you could design and develop the user interface, while your background in psychology could inform the adaptive learning algorithms used by the platform.", max_lines=3), | |
gr.Audio(Lable="Speaker Wav", source="microphone", type="filepath"), | |
gr.Radio(label="Language", choices=tts.languages, value="en")] | |
outputs = gr.Audio(label="Output") | |
demo = gr.Interface(fn=text_to_speech, inputs=inputs, outputs=outputs) | |
demo.launch(debug=True) |