app.py

import os
import time

import gradio as gr
from pydub import AudioSegment
from transformers import pipeline

is_hf = os.getenv("SYSTEM") == "spaces"

generate_kwargs = {
    "language": "Japanese",
    "do_sample": False,
    "num_beams": 1,
    "no_repeat_ngram_size": 3,
}


model_dict = {
    "whisper-large-v2": "openai/whisper-large-v2",
    "whisper-large-v3": "openai/whisper-large-v3",
    "whisper-large-v3-turbo": "openai/whisper-large-v3-turbo",
    "kotoba-whisper-v1.0": "kotoba-tech/kotoba-whisper-v1.0",
    "kotoba-whisper-v2.0": "kotoba-tech/kotoba-whisper-v2.0",
    "galgame-whisper-wip": (
        "litagin/galgame-whisper-wip"
        if is_hf
        else "../whisper_finetune/galgame-whisper"
    ),
}

# Download models
for model in model_dict.values():
    pipeline("automatic-speech-recognition", model=model)


def transcribe_common(audio: str, model: str) -> tuple[str, float]:
    # Get duration of audio
    duration = AudioSegment.from_file(audio).duration_seconds
    if duration > 15:
        return "Audio too long, limit is 15 seconds", 0
    start_time = time.time()
    pipe = pipeline("automatic-speech-recognition", model=model)
    end_time = time.time()
    return pipe(audio, generate_kwargs=generate_kwargs)["text"], end_time - start_time


def transcribe_large_v2(audio) -> tuple[str, float]:
    return transcribe_common(audio, model_dict["whisper-large-v2"])


def transcribe_large_v3(audio) -> tuple[str, float]:
    return transcribe_common(audio, model_dict["whisper-large-v3"])


def transcribe_large_v3_turbo(audio) -> tuple[str, float]:
    return transcribe_common(audio, model_dict["whisper-large-v3-turbo"])


def transcribe_kotoba_v1(audio) -> tuple[str, float]:
    return transcribe_common(audio, model_dict["kotoba-whisper-v1.0"])


def transcribe_kotoba_v2(audio) -> tuple[str, float]:
    return transcribe_common(audio, model_dict["kotoba-whisper-v2.0"])


def transcribe_galgame_whisper(audio) -> tuple[str, float]:
    return transcribe_common(audio, model_dict["galgame-whisper-wip"])


initial_md = """
# Galgame-Whisper (WIP) Demo

- 日本語のみ対応
- 他の書き起こしとついでに比較できるようにいろいろ入れた
- 現在0.1エポックくらい
- 速度はCPUです
- 音声は15秒まで
"""

with gr.Blocks() as app:
    audio = gr.Audio(type="filepath")
    gr.Markdown("### Kotoba-Whisper-V1.0")
    with gr.Row():
        with gr.Column():
            gr.Markdown("### Whisper-Large-V2")
            button_v2 = gr.Button("Transcribe with Whisper-Large-V2")
            output_v2 = gr.Textbox()
            time_v2 = gr.Textbox("Time taken")
        with gr.Column():
            gr.Markdown("### Whisper-Large-V3")
            button_v3 = gr.Button("Transcribe with Whisper-Large-V3")
            output_v3 = gr.Textbox()
            time_v3 = gr.Textbox("Time taken")
        with gr.Column():
            gr.Markdown("### Whisper-Large-V3-Turbo")
            button_v3_turbo = gr.Button("Transcribe with Whisper-Large-V3-Turbo")
            output_v3_turbo = gr.Textbox()
            time_v3_turbo = gr.Textbox()
    with gr.Row():
        with gr.Column():
            gr.Markdown("### Kotoba-Whisper-V1.0")
            button_kotoba_v1 = gr.Button("Transcribe with Kotoba-Whisper-V1.0")
            output_kotoba_v1 = gr.Textbox()
            time_kotoba_v1 = gr.Textbox("Time taken")
        with gr.Column():
            gr.Markdown("### Kotoba-Whisper-V2.0")
            button_kotoba_v2 = gr.Button("Transcribe with Kotoba-Whisper-V2.0")
            output_kotoba_v2 = gr.Textbox()
            time_kotoba_v2 = gr.Textbox("Time taken")
    with gr.Row():
        with gr.Column():
            gr.Markdown("### Galgame-Whisper (WIP)")
            button_galgame = gr.Button("Transcribe with Galgame-Whisper (WIP)")
            output_galgame = gr.Textbox()
            time_galgame = gr.Textbox("Time taken")

    button_v2.click(transcribe_large_v2, inputs=audio, outputs=[output_v2, time_v2])
    button_v3.click(transcribe_large_v3, inputs=audio, outputs=[output_v3, time_v3])
    button_v3_turbo.click(
        transcribe_large_v3_turbo,
        inputs=audio,
        outputs=[output_v3_turbo, time_v3_turbo],
    )
    button_kotoba_v1.click(
        transcribe_kotoba_v1, inputs=audio, outputs=[output_kotoba_v1, time_kotoba_v1]
    )
    button_kotoba_v2.click(
        transcribe_kotoba_v2, inputs=audio, outputs=[output_kotoba_v2, time_kotoba_v2]
    )
    button_galgame.click(
        transcribe_galgame_whisper,
        inputs=audio,
        outputs=[output_galgame, time_galgame],
    )

app.launch(inbrowser=True)