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import gradio as gr
from src.transcriber import transcriber
def main():
with gr.Blocks(title='multilang-asr-transcriber', delete_cache=(86400, 86400), theme=gr.themes.Base()) as demo:
gr.Markdown('## Multilang ASR Transcriber')
gr.Markdown('An automatic speech recognition tool using [faster-whisper](https://github.com/SYSTRAN/faster-whisper). Supports multilingual video transcription and translation to english. Users may set the max words per line.')
with gr.Tabs(selected="video") as tabs:
with gr.Tab("Video", id="video"):
with gr.Row():
with gr.Column():
video = True
file = gr.File(file_types=["video"],type="filepath", label="Upload a video")
file_type = gr.Radio(choices=["video"], value="video", label="File Type", visible=False)
max_words_per_line = gr.Number(value=6, label="Max words per line")
task = gr.Radio(choices=["transcribe", "translate"], value="transcribe", label="Select Task")
model_version = gr.Radio(choices=["deepdml/faster-whisper-large-v3-turbo-ct2",
"turbo",
"large-v3"], value="deepdml/faster-whisper-large-v3-turbo-ct2", label="Select Model")
transcribe_btn = gr.Button(value="Transcribe", variant="primary")
with gr.Column():
text_output = gr.Textbox(label="SRT Text transcription")
srt_file = gr.File(value=None, file_count="single", type="filepath", file_types=[".srt"], label="SRT file")
text_clean_output = gr.Textbox(label="Text transcription")
transcribe_btn.click(
fn=transcriber,
inputs=[file, file_type, max_words_per_line, task, model_version],
outputs=[text_output, srt_file, text_clean_output]
)
with gr.Tab("Audio", id = "audio"):
with gr.Row():
with gr.Column():
video = False
file = gr.File(file_types=["audio"],type="filepath", label="Upload an audio file")
file_type = gr.Radio(choices=["audio"], value="audio", label="File Type", visible=False)
max_words_per_line = gr.Number(value=6, label="Max words per line")
task = gr.Radio(choices=["transcribe", "translate"], value="transcribe", label="Select Task")
model_version = gr.Radio(choices=["deepdml/faster-whisper-large-v3-turbo-ct2",
"turbo",
"large-v3"], value="deepdml/faster-whisper-large-v3-turbo-ct2", label="Select Model")
transcribe_btn = gr.Button(value="Transcribe", variant="primary")
with gr.Column():
text_output = gr.Textbox(label="SRT Text transcription")
srt_file = gr.File(value=None, file_count="single", type="filepath", file_types=[".srt"], label="SRT file")
text_clean_output = gr.Textbox(label="Text transcription")
transcribe_btn.click(
fn=transcriber,
inputs=[file, file_type, max_words_per_line, task, model_version],
outputs=[text_output, srt_file, text_clean_output]
)
demo.launch()
if __name__ == '__main__':
main() |