main.py

#!/usr/bin/python3
# -*- coding: utf-8 -*-
import argparse

import gradio as gr

from examples import examples
from project_settings import project_path


def get_args():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--examples_dir",
        default=(project_path / "data/examples").as_posix(),
        type=str
    )
    parser.add_argument(
        "--trained_model_dir",
        default=(project_path / "trained_models").as_posix(),
        type=str
    )
    args = parser.parse_args()
    return args


def update_model_dropdown(language: str):
    if language in language_to_models:
        choices = language_to_models[language]
        return gr.Dropdown(
            choices=choices,
            value=choices[0],
            interactive=True,
        )

    raise ValueError(f"Unsupported language: {language}")


def main():
    title = "# Automatic Speech Recognition with Next-gen Kaldi"

    language_choices = ["Chinese"]

    language_to_models = {
        "Chinese": ["None"]
    }

    # components
    language_radio = gr.Radio(
        label="Language",
        choices=language_choices,
        value=language_choices[0],
    )
    model_dropdown = gr.Dropdown(
        choices=language_to_models[language_choices[0]],
        label="Select a model",
        value=language_to_models[language_choices[0]][0],
    )

    language_radio.change(
        update_model_dropdown,
        inputs=language_radio,
        outputs=model_dropdown,
    )


    # blocks
    with gr.Blocks() as blocks:
        gr.Markdown(value=title)

        with gr.Tabs():
            with gr.TabItem("Upload from disk"):
                uploaded_file = gr.Audio(
                    sources=["upload"],
                    type="filepath",
                    label="Upload from disk",
                )
                upload_button = gr.Button("Submit for recognition")
                uploaded_output = gr.Textbox(label="Recognized speech from uploaded file")
                uploaded_html_info = gr.HTML(label="Info")

                gr.Examples(
                    examples=examples,
                    inputs=[
                        language_radio,
                        model_dropdown,
                        decoding_method_radio,
                        num_active_paths_slider,
                        punct_radio,
                        uploaded_file,
                    ],
                    outputs=[uploaded_output, uploaded_html_info],
                    fn=process_uploaded_file,
                )

    blocks.queue().launch()

    return


if __name__ == "__main__":
    main()