Timed text extraction from Taiwanese Kua-á-hì TV series

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Huang, Tzu-Hung, Tsai, Yun-En, Hung, Yun-Ning, Wu, Chih-Wei, Wei, I-Chieh, Su, Li
Format: Preprint
Published: 2026
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866911350163243008
author Huang, Tzu-Hung
Tsai, Yun-En
Hung, Yun-Ning
Wu, Chih-Wei
Wei, I-Chieh
Su, Li
author_facet Huang, Tzu-Hung
Tsai, Yun-En
Hung, Yun-Ning
Wu, Chih-Wei
Wei, I-Chieh
Su, Li
contents Taiwanese opera (Kua-á-hì), a major form of local theatrical tradition, underwent extensive television adaptation notably by pioneers like Iûnn Lē-hua. These videos, while potentially valuable for in-depth studies of Taiwanese opera, often have low quality and require substantial manual effort during data preparation. To streamline this process, we developed an interactive system for real-time OCR correction and a two-step approach integrating OCR-driven segmentation with Speech and Music Activity Detection (SMAD) to efficiently identify vocal segments from archival episodes with high precision. The resulting dataset, consisting of vocal segments and corresponding lyrics, can potentially supports various MIR tasks such as lyrics identification and tune retrieval. Code is available at https://github.com/z-huang/ocr-subtitle-editor .
format Preprint
id arxiv_https___arxiv_org_abs_2601_00299
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Timed text extraction from Taiwanese Kua-á-hì TV series
Huang, Tzu-Hung
Tsai, Yun-En
Hung, Yun-Ning
Wu, Chih-Wei
Wei, I-Chieh
Su, Li
Sound
Multimedia
Taiwanese opera (Kua-á-hì), a major form of local theatrical tradition, underwent extensive television adaptation notably by pioneers like Iûnn Lē-hua. These videos, while potentially valuable for in-depth studies of Taiwanese opera, often have low quality and require substantial manual effort during data preparation. To streamline this process, we developed an interactive system for real-time OCR correction and a two-step approach integrating OCR-driven segmentation with Speech and Music Activity Detection (SMAD) to efficiently identify vocal segments from archival episodes with high precision. The resulting dataset, consisting of vocal segments and corresponding lyrics, can potentially supports various MIR tasks such as lyrics identification and tune retrieval. Code is available at https://github.com/z-huang/ocr-subtitle-editor .
title Timed text extraction from Taiwanese Kua-á-hì TV series
topic Sound
Multimedia
url https://arxiv.org/abs/2601.00299