app.py

import gradio as gr
from zeroshot import (
    process,
    WORD_SCORE_DEFAULT_IF_LM,
    WORD_SCORE_DEFAULT_IF_NOLM,
    LM_SCORE_DEFAULT,
)

with gr.Blocks(css="style.css") as demo:
    gr.Markdown(
        "<p align='center' style='font-size: 20px;'>MMS Zero-shot ASR Demo. See our arXiV <a href='https://arxiv.org/'>paper</a> for model details.</p>"
    )
    gr.HTML(
        """<center>The demo works on input audio in any language, as long as you provide a list of words or sentences for that language and an optional n-gram language model (even a simple 1-gram model will work!) to help with accuracy.<br>We recommend having a minimum of 5000 distinct words in the textfile to acheive a good performance.</center>"""
    )
    with gr.Row():
        with gr.Column():
            audio = gr.Audio(label="Audio Input\n(use microphone or upload a file)")

            with gr.Row():
                words_file = gr.File(label="Text Data")
                lm_file = gr.File(label="Language Model\n(optional)")

            with gr.Accordion("Advanced Settings", open=False):
                gr.Markdown(
                    "The following parameters are used for beam-search decoding. Use the default values if you are not sure."
                )
                with gr.Row():
                    with gr.Column():
                        wscore_usedefault = gr.Checkbox(
                            label="Use Default Word Insertion Score", value=True
                        )
                        wscore = gr.Slider(
                            minimum=-10.0,
                            maximum=10.0,
                            value=WORD_SCORE_DEFAULT_IF_NOLM,
                            step=0.1,
                            interactive=False,
                            label="Word Insertion Score",
                        )

                    with gr.Column():
                        lmscore_usedefault = gr.Checkbox(
                            label="Use Default Language Model Score", value=True
                        )
                        lmscore = gr.Slider(
                            minimum=-10.0,
                            maximum=10.0,
                            value=0,
                            step=0.1,
                            interactive=False,
                            label="Language Model Score",
                        )
            btn = gr.Button("Submit", elem_id="submit")

            @gr.on(
                inputs=[wscore_usedefault, lmscore_usedefault, lm_file],
                outputs=[wscore, lmscore],
            )
            def update_slider(ws, ls, lm):

                ws_slider = gr.Slider(
                    minimum=-10.0,
                    maximum=10.0,
                    value=LM_SCORE_DEFAULT if lm is not None else 0,
                    step=0.1,
                    interactive=not ws,
                    label="Word Insertion Score",
                )
                ls_slider = gr.Slider(
                    minimum=-10.0,
                    maximum=10.0,
                    value=WORD_SCORE_DEFAULT_IF_NOLM
                    if lm is None
                    else WORD_SCORE_DEFAULT_IF_LM,
                    step=0.1,
                    interactive=not ls,
                    label="Language Model Score",
                )
                return ws_slider, ls_slider

        with gr.Column():
            text = gr.Textbox(label="Transcript")
            with gr.Accordion("Logs", open=False):
                logs = gr.Textbox(show_label=False)

    # hack 
    reference = gr.Textbox(label="Reference Transcript", visible=False)

    btn.click(
        process,
        inputs=[
            audio,
            words_file,
            lm_file,
            wscore,
            lmscore,
            wscore_usedefault,
            lmscore_usedefault,
            reference
        ],
        outputs=[text, logs],
    )

    # Examples
    gr.Examples(
        examples=[
            # ["upload/english/english.mp3", "upload/english/c4_25k_sentences.txt"],
            ["upload/english/english.mp3", "upload/english/c4_10k_sentences.txt", " This is going to look at the code that we have in our configuration that we've already exported and compare it to our database, and we want to import"],
            ["upload/english/english.mp3", "upload/english/c4_5k_sentences.txt", " This is going to look at the code that we have in our configuration that we've already exported and compare it to our database, and we want to import"],
            ["upload/english/english.mp3", "upload/english/cv8_top10k_words.txt", " This is going to look at the code that we have in our configuration that we've already exported and compare it to our database, and we want to import"],
        ],
        inputs=[audio, words_file, reference],
        label="English",
    )
    gr.Examples(
        examples=[
            # ["upload/english/english.mp3", "upload/english/c4_25k_sentences.txt"],
            ["upload/ligurian/ligurian_1.mp3", "upload/ligurian/zenamt_10k_sentences.txt", "I mæ colleghi m’an domandou d’aggiuttâli à fâ unna preuva co-o zeneise pe vedde s’o fonçioña."],
            ["upload/ligurian/ligurian_2.mp3", "upload/ligurian/zenamt_10k_sentences.txt", "Staseia vaggo à çenâ con mæ moggê e doî amixi che de chì à quarche settemaña faian stramuo feua stato."],
            ["upload/ligurian/ligurian_3.mp3", "upload/ligurian/zenamt_5k_sentences.txt", "Pe inandiâ o pesto ghe veu o baxaicò, i pigneu, l’euio, o formaggio, l’aggio e a sâ."],
        ],
        inputs=[audio, words_file, reference],
        label="Ligurian",
    )

demo.launch()