| 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"): | |
| 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") | |
| 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", "large-v3"], value="deepdml/faster-whisper-large-v3-turbo-ct2", label="Select Model") | |
| text_output = gr.Textbox(label="SRT Text transcription", show_copy_button=True) | |
| srt_file = gr.File(file_count="single", type="filepath", file_types=[".srt"], label="SRT file") | |
| text_clean_output = gr.Textbox(label="Text transcription", show_copy_button=True) | |
| gr.Interface(transcriber, | |
| inputs=[file, file_type, max_words_per_line, task, model_version], | |
| outputs=[text_output, srt_file, text_clean_output], | |
| allow_flagging="never") | |
| with gr.Tab("Audio", id = "audio"): | |
| 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") | |
| 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", "large-v3"], value="deepdml/faster-whisper-large-v3-turbo-ct2", label="Select Model") | |
| text_output = gr.Textbox(label="SRT Text transcription", show_copy_button=True) | |
| srt_file = gr.File(file_count="single", type="filepath", file_types=[".srt"], label="SRT file") | |
| text_clean_output = gr.Textbox(label="Text transcription", show_copy_button=True) | |
| gr.Interface(transcriber, | |
| inputs=[file, file_type, max_words_per_line, task, model_version], | |
| outputs=[text_output, srt_file, text_clean_output], | |
| allow_flagging="never") | |
| demo.launch() | |
| if __name__ == '__main__': | |
| main() |