app.py

# Copyright (c) 2023 Amphion.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree

import subprocess

command_to_run = "cd ./modules/monotonic_align;mkdir -p monotonic_align;python setup.py build_ext --inplace;cd /home/user/app"
subprocess.check_output(command_to_run, shell=True, text=True)

import gradio as gr
import os
import inference

SUPPORTED_SPEAKERS = {
    "Cori Samuel":"hifitts_92",
    "Phil Benson":"hifitts_6097",
    "Mike Pelton":"hifitts_6670",
    "Tony Oliva":"hifitts_6671",
    "Maria Kasper":"hifitts_8051",
    "John Van Stan":"hifitts_9017",
    "Helen Taylor":"hifitts_9136",
    "Sylviamb":"hifitts_11614", 
    "Celine Major":"hifitts_11697",
    "LikeManyWaters":"hifitts_12787"
}


def tts_inference(
    input_text,
    target_speaker,
    duration
):
    ### Target Speaker ###
    target_speaker = SUPPORTED_SPEAKERS[target_speaker]
    
    args_list = ["--config", "./egs/tts/vits_hifitts/exp_config.json"]
    args_list += ["--checkpoint_path", "./expdir/checkpoint/latest-checkpoint"]
    args_list += ["--speaker_name_1", target_speaker]
    args_list += ["--speaker_name_2", None]
    args_list += ["--text", input_text]
    args_list += ["--mode","single"]
    args_list += ["--duration_control",str(float(duration))]
    args_list += ["--output_dir", "result"]
    args_list += ["--log_level", "debug"]

    os.environ["WORK_DIR"] = "./"
    inference.main(args_list)

    ### Display ###
    result_file = os.path.join(
        "result/single/test_pred.wav"
    )
    return result_file

def tc_inference(
    input_text,
    target_speaker_1,
    target_speaker_2,
    confusion_degree,
    duration
):
    ### Target Speaker ###
    target_speaker_1 = SUPPORTED_SPEAKERS[target_speaker_1]
    if target_speaker_2 is not None:
        target_speaker_2 = SUPPORTED_SPEAKERS[target_speaker_2]
    
    args_list = ["--config", "./egs/tts/vits_hifitts/exp_config.json"]
    args_list += ["--checkpoint_path", "./expdir/checkpoint/latest-checkpoint"]
    args_list += ["--speaker_name_1", target_speaker_1]
    args_list += ["--speaker_name_2", target_speaker_2]
    args_list += ["--alpha", str(float(confusion_degree))]
    args_list += ["--text", input_text]
    args_list += ["--mode","single"]
    args_list += ["--duration_control",str(float(duration))]
    args_list += ["--output_dir", "result"]
    args_list += ["--log_level", "debug"]

    os.environ["WORK_DIR"] = "./"
    inference.main(args_list)

    ### Display ###
    source_speaker_1 = os.path.join(
        "result/single/s1.wav"
    )
    source_speaker_2 = os.path.join(
        "result/single/s2.wav"
    )
    result_file = os.path.join(
        "result/single/test_pred.wav"
    )
    
    return source_speaker_1, source_speaker_2, result_file

# Section 1: TTS
tts_demo_inputs = [
    gr.Textbox(
        label="Input Text",
        type="text",
        placeholder="Type something here.."
    ),
    gr.Radio(
        choices=list(SUPPORTED_SPEAKERS.keys()),
        label="Target Speaker",
        value="Cori Samuel"
    ),
    gr.Slider(
        1,
        5,
        value=1,
        step=0.25,
        label="Speaking Rate",
        info="As the step number increases, the speaking rate will be slower.",
    )
]

tts_demo_output = gr.Audio(label="Generated Speech")


# Section 2: Timbre confusion
tc_demo_inputs = [
    gr.Textbox(
        label="Input Text",
        type="text",
        placeholder="Type something here.."
    ),
    gr.Radio(
        choices=list(SUPPORTED_SPEAKERS.keys()),
        label="Target Speaker 1",
        value="Cori Samuel"
    ),
    gr.Radio(
        choices=list(SUPPORTED_SPEAKERS.keys()),
        label="Target Speaker 2",
        value="Phil Benson"
    ),
    gr.Slider(
        0,
        1,
        value=0.5,
        step=0.1,
        label="Fusion Degree",
        info="As the step number increases, the generated voice will be more similar to speaker 2.",
    ),
    gr.Slider(
        1,
        5,
        value=1,
        step=0.25,
        label="Speaking Rate",
        info="As the step number increases, the speaking rate will be slower.",
    )
]

tc_demo_outputs = [
    gr.Audio(label="Target Speaker 1"),
    gr.Audio(label="Target Speaker 2"),
    gr.Audio(label="Interpolated Speech")
]

    

with gr.Blocks() as demo:
    gr.Interface(
        fn=tts_inference,
        inputs=tts_demo_inputs,
        outputs=tts_demo_output,
        title="Amphion Text-to-Speech",
        description="This demo offers an Amphion TTS pretrained model (VITS) for you to explore."
    )
    
    gr.Interface(
        fn=tc_inference,
        inputs=tc_demo_inputs,
        outputs=tc_demo_outputs,
        title="Voice Fusion",
        description="In this section, you can choose two speakers to create a voice mix. Adjust the ‘Fusion Degree’ slider to customize your desired mix ratio between the two speakers."
    )

    demo.queue()
    demo.launch()

# if __name__ == "__main__":
#     demo.launch(share=True)