6Simple9/ChatTTS-OpenVoice

1import spaces2import os3import random4import argparse5 6import torch7import gradio as gr8import numpy as np9 10import ChatTTS11 12from OpenVoice import se_extractor13from OpenVoice.api import ToneColorConverter14import soundfile15 16print("loading ChatTTS model...")17chat = ChatTTS.Chat()18chat.load_models()19 20 21def generate_seed():22    new_seed = random.randint(1, 100000000)23    return {24        "__type__": "update",25        "value": new_seed26        }27 28@spaces.GPU29def chat_tts(text, temperature, top_P, top_K, audio_seed_input, text_seed_input, refine_text_flag, refine_text_input, output_path=None):30 31    torch.manual_seed(audio_seed_input)32    rand_spk = torch.randn(768)33    params_infer_code = {34        'spk_emb': rand_spk, 35        'temperature': temperature,36        'top_P': top_P,37        'top_K': top_K,38        }39    params_refine_text = {'prompt': '[oral_2][laugh_0][break_6]'}40    41    torch.manual_seed(text_seed_input)42 43    if refine_text_flag:44        if refine_text_input:45           params_refine_text['prompt'] = refine_text_input46        text = chat.infer(text, 47                          skip_refine_text=False,48                          refine_text_only=True,49                          params_refine_text=params_refine_text,50                          params_infer_code=params_infer_code51                          )52        print("Text has been refined!")53    54    wav = chat.infer(text, 55                     skip_refine_text=True, 56                     params_refine_text=params_refine_text, 57                     params_infer_code=params_infer_code58                     )59    60    audio_data = np.array(wav[0]).flatten()61    sample_rate = 2400062    text_data = text[0] if isinstance(text, list) else text63 64    if output_path is None:65        return [(sample_rate, audio_data), text_data]66    else:67        soundfile.write(output_path, audio_data, sample_rate)68        return text_data69 70# OpenVoice Clone71ckpt_converter = 'OpenVoice/checkpoints/converter'72device = "cuda:0" if torch.cuda.is_available() else "cpu"73 74tone_color_converter = ToneColorConverter(f'{ckpt_converter}/config.json', device=device)75tone_color_converter.load_ckpt(f'{ckpt_converter}/checkpoint.pth')76 77def generate_audio(text, audio_ref, temperature, top_P, top_K, audio_seed_input, text_seed_input, refine_text_flag, refine_text_input):78    save_path = "output.wav"79    80    if audio_ref != "" :81      # Run the base speaker tts82      src_path = "tmp.wav"83      text_data = chat_tts(text, temperature, top_P, top_K, audio_seed_input, text_seed_input, refine_text_flag, refine_text_input, src_path)84      print("Ready for voice cloning!")85    86      source_se, audio_name = se_extractor.get_se(src_path, tone_color_converter, target_dir='processed', vad=True)87      reference_speaker = audio_ref88      target_se, audio_name = se_extractor.get_se(reference_speaker, tone_color_converter, target_dir='processed', vad=True)89 90      print("Get voices segment!")91    92      # Run the tone color converter93      # convert from file94      tone_color_converter.convert(95        audio_src_path=src_path,96        src_se=source_se,97        tgt_se=target_se,98        output_path=save_path)99    else:100      chat_tts(text, temperature, top_P, top_K, audio_seed_input, text_seed_input, refine_text_flag, refine_text_input, save_path)101 102    print("Finished!")103 104    return [save_path, text_data]105 106 107with gr.Blocks() as demo:108    gr.Markdown("# <center>🥳 ChatTTS x OpenVoice 🥳</center>")109    gr.Markdown("## <center>🌟 Make it sound super natural and switch it up to any voice you want, nailing the mood and tone also!🌟 </center>")110 111    default_text = "Today a man knocked on my door and asked for a small donation toward the local swimming pool. I gave him a glass of water."        112    text_input = gr.Textbox(label="Input Text", lines=4, placeholder="Please Input Text...", value=default_text)113 114 115    default_refine_text = "[oral_2][laugh_0][break_6]"    116    refine_text_input = gr.Textbox(label="Refine Prompt", lines=1, placeholder="Please Refine Prompt...", value=default_refine_text)117    refine_text_checkbox = gr.Checkbox(label="Refine text", info="use oral_(0-9), laugh_(0-2), break_(0-7).'oral' means add filler words, 'laugh' means add laughter, and 'break' means add a pause.", value=True)118    with gr.Column():    119        voice_ref = gr.Audio(label="Reference Audio", type="filepath", value="Examples/speaker.mp3")120 121    with gr.Row():122        temperature_slider = gr.Slider(minimum=0.00001, maximum=1.0, step=0.00001, value=0.3, label="Audio temperature")123        top_p_slider = gr.Slider(minimum=0.1, maximum=0.9, step=0.05, value=0.7, label="top_P")124        top_k_slider = gr.Slider(minimum=1, maximum=20, step=1, value=20, label="top_K")125 126    with gr.Row():127        audio_seed_input = gr.Number(value=42, label="Speaker Seed")128        generate_audio_seed = gr.Button("\U0001F3B2")129        text_seed_input = gr.Number(value=42, label="Text Seed")130        generate_text_seed = gr.Button("\U0001F3B2")131 132    generate_button = gr.Button("Generate")133        134    text_output = gr.Textbox(label="Refined Text", interactive=False)135    audio_output = gr.Audio(label="Output Audio")136 137    generate_audio_seed.click(generate_seed, 138                              inputs=[], 139                              outputs=audio_seed_input)140        141    generate_text_seed.click(generate_seed, 142                             inputs=[], 143                             outputs=text_seed_input)144        145    generate_button.click(generate_audio, 146                          inputs=[text_input, voice_ref, temperature_slider, top_p_slider, top_k_slider, audio_seed_input, text_seed_input, refine_text_checkbox, refine_text_input], 147                          outputs=[audio_output,text_output])148 149parser = argparse.ArgumentParser(description='ChatTTS-OpenVoice Launch')150parser.add_argument('--server_name', type=str, default='0.0.0.0', help='Server name')151parser.add_argument('--server_port', type=int, default=8080, help='Server port')152args = parser.parse_args()153 154# demo.launch(server_name=args.server_name, server_port=args.server_port, inbrowser=True)155 156if __name__ == '__main__':157    demo.launch()