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| from subprocess import call | |
| import gradio as gr | |
| import os | |
| from TTS.api import TTS | |
| # List available 🐸TTS models and choose the first one | |
| all_models = TTS.list_models() | |
| # for model in all_models: | |
| # print(model) | |
| # print("Using model: ", all_models[0]) | |
| model_name = all_models[0] | |
| # Init TTS | |
| print("Downloading model...", '') | |
| voiceCloneModel = TTS('tts_models/multilingual/multi-dataset/your_tts') | |
| def run_cmd(command): | |
| try: | |
| print(command) | |
| call(command) | |
| except KeyboardInterrupt: | |
| print("Process interrupted") | |
| sys.exit(1) | |
| def inference(text, speaker): | |
| if (speaker == 'Speaker-1'): | |
| speaker = 'input/amitabh.mp3' | |
| elif (speaker == 'Speaker-2'): | |
| speaker = 'input/amrish.mp3' | |
| elif (speaker == 'Speaker-3'): | |
| speaker = 'input/obama.mp3' | |
| elif (speaker == 'Speaker-4'): | |
| speaker = 'input/trump.wav' | |
| else: | |
| speaker = 'input/z-default.wav' | |
| # print("speaker: ", speaker) | |
| # cmd = ['tts', '--text', text, '--out_path', 'output/tts_output.wav'] | |
| # run_cmd(cmd) | |
| # Text to speech to a file | |
| # tts = TTS(model_name="tts_models/multilingual/multi-dataset/your_tts", | |
| # progress_bar=False, gpu=True) | |
| voiceCloneModel.tts_to_file(text, speaker_wav=speaker, | |
| language="en", file_path="output/output.wav") | |
| # for i in range(len(tts.languages)): | |
| # tts.tts_to_file(text=text, | |
| # speaker=tts.speakers[i], language=tts.languages[0], file_path='output/output-'+str(i)+'.wav') | |
| return 'output/output.wav' | |
| inputs = [gr.inputs.Textbox(lines=5, label="Input Text"), | |
| gr.inputs.Dropdown(['Speaker-1', 'Speaker-2', 'Speaker-3', | |
| 'Speaker-4'], label="Model") | |
| ] | |
| outputs = gr.outputs.Audio(type="filepath", label="Output Audio") | |
| title = "Text To Speech" | |
| description = "An example of using TTS to generate speech from text." | |
| article = "" | |
| examples = [ | |
| ["This is an open-source library that generates synthetic speech"] | |
| ] | |
| gr.Interface( | |
| inference, | |
| inputs, | |
| outputs, | |
| verbose=True, | |
| title=title, | |
| description=description, | |
| article=article, | |
| examples=examples, | |
| enable_queue=True, | |
| allow_flagging="never", | |
| ).launch(debug=True) | |