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#!/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()
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