File size: 3,885 Bytes
23e6529
 
 
 
 
1d91c75
23e6529
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1d91c75
 
23e6529
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
import os
import random
import argparse

import torch
import gradio as gr
import numpy as np

import ChatTTS

print("loading ChatTTS model...")
chat = ChatTTS.Chat()
chat.load_models()

def generate_seed():
    new_seed = random.randint(1, 100000000)
    return {
        "__type__": "update",
        "value": new_seed
        }


def generate_audio(text, temperature, top_P, top_K, audio_seed_input, text_seed_input, refine_text_flag):

    torch.manual_seed(audio_seed_input)
    rand_spk = torch.randn(768)
    params_infer_code = {
        'spk_emb': rand_spk, 
        'temperature': temperature,
        'top_P': top_P,
        'top_K': top_K,
        }
    params_refine_text = {'prompt': '[oral_2][laugh_0][break_6]'}
    
    torch.manual_seed(text_seed_input)

    if refine_text_flag:
        text = chat.infer(text, 
                          skip_refine_text=False,
                          refine_text_only=True,
                          params_refine_text=params_refine_text,
                          params_infer_code=params_infer_code
                          )
    
    wav = chat.infer(text, 
                     skip_refine_text=True, 
                     params_refine_text=params_refine_text, 
                     params_infer_code=params_infer_code
                     )
    
    audio_data = np.array(wav[0]).flatten()
    sample_rate = 24000
    text_data = text[0] if isinstance(text, list) else text

    return [(sample_rate, audio_data), text_data]


def main():

    with gr.Blocks() as demo:
        gr.Markdown("# ChatTTS Webui")
        gr.Markdown("ChatTTS Model: [2noise/ChatTTS](https://github.com/2noise/ChatTTS)")

        default_text = "四川美食确实以辣闻名,但也有不辣的选择。比如甜水面、赖汤圆、蛋烘糕、叶儿粑等,这些小吃口味温和,甜而不腻,也很受欢迎。"        
        text_input = gr.Textbox(label="Input Text", lines=4, placeholder="Please Input Text...", value=default_text)

        with gr.Row():
            refine_text_checkbox = gr.Checkbox(label="Refine text", value=True)
            temperature_slider = gr.Slider(minimum=0.00001, maximum=1.0, step=0.00001, value=0.3, label="Audio temperature")
            top_p_slider = gr.Slider(minimum=0.1, maximum=0.9, step=0.05, value=0.7, label="top_P")
            top_k_slider = gr.Slider(minimum=1, maximum=20, step=1, value=20, label="top_K")

        with gr.Row():
            audio_seed_input = gr.Number(value=42, label="Audio Seed")
            generate_audio_seed = gr.Button("\U0001F3B2")
            text_seed_input = gr.Number(value=42, label="Text Seed")
            generate_text_seed = gr.Button("\U0001F3B2")

        generate_button = gr.Button("Generate")
        
        text_output = gr.Textbox(label="Output Text", interactive=False)
        audio_output = gr.Audio(label="Output Audio")

        generate_audio_seed.click(generate_seed, 
                                  inputs=[], 
                                  outputs=audio_seed_input)
        
        generate_text_seed.click(generate_seed, 
                                 inputs=[], 
                                 outputs=text_seed_input)
        
        generate_button.click(generate_audio, 
                              inputs=[text_input, temperature_slider, top_p_slider, top_k_slider, audio_seed_input, text_seed_input, refine_text_checkbox], 
                              outputs=[audio_output, text_output])

    parser = argparse.ArgumentParser(description='ChatTTS demo Launch')
    parser.add_argument('--server_name', type=str, default='0.0.0.0', help='Server name')
    parser.add_argument('--server_port', type=int, default=8080, help='Server port')
    args = parser.parse_args()

    demo.launch(server_name=args.server_name, server_port=args.server_port, inbrowser=True)


if __name__ == '__main__':
    main()