A language model using variable length tokens for open-vocabulary Hangul text recognition

被引:1
|
作者
Ryu, SH [1 ]
Kim, JH [1 ]
机构
[1] Korea Adv Inst Sci & Technol, Div Comp Sci 373 1, Taejon 305701, South Korea
关键词
language model; character recognition; hangul recognition; open-vocabulary; word recognition;
D O I
10.1016/j.patcog.2003.12.004
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We propose a novel language model for Hangul text recognition. Without relying on prior linguistic knowledge in training, the proposed model learns variable length Hangul character sequences, which comprise the elementary tokens of Korean language, and their probabilities from statistics of a raw text corpus. Experiments in handwritten Hangul recognition shows that the proposed language model is effective in postprocessing of recognition results. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:1549 / 1552
页数:4
相关论文
共 50 条
  • [31] Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach
    Schwartz, H. Andrew
    Eichstaedt, Johannes C.
    Kern, Margaret L.
    Dziurzynski, Lukasz
    Ramones, Stephanie M.
    Agrawal, Megha
    Shah, Achal
    Kosinski, Michal
    Stillwell, David
    Seligman, Martin E. P.
    Ungar, Lyle H.
    PLOS ONE, 2013, 8 (09):
  • [32] Localized Vision-Language Matching for Open-vocabulary Object Detection
    Bravo, Maria A.
    Mittal, Sudhanshu
    Brox, Thomas
    PATTERN RECOGNITION, DAGM GCPR 2022, 2022, 13485 : 393 - 408
  • [33] Variable length language model for Chinese character recognition
    Zhang, S
    Wu, XL
    ADVANCES IN MULTIMODAL INTERFACES - ICMI 2000, PROCEEDINGS, 2000, 1948 : 267 - 271
  • [34] Open-vocabulary spoken term detection using graphone-based hybrid recognition systems
    Akbacak, Murat
    Vergyri, Dimitra
    Stolcke, Andreas
    2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-12, 2008, : 5240 - 5243
  • [35] A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-Language Model
    Xu, Mengde
    Zhang, Zheng
    Wei, Fangyun
    Lin, Yutong
    Cao, Yue
    Hu, Han
    Bai, Xiang
    COMPUTER VISION, ECCV 2022, PT XXIX, 2022, 13689 : 736 - 753
  • [36] Open-vocabulary spoken utterance retrieval using confusion networks
    Hori, Takaaki
    Hetherington, I. Lee
    Hazen, Timothy J.
    Glass, James R.
    2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL IV, PTS 1-3, 2007, : 73 - +
  • [37] Learning Open-vocabulary Semantic Segmentation Models From Natural Language Supervision
    Xu, Jilan
    Hou, Junlin
    Zhang, Yuejie
    Feng, Rui
    Wang, Yi
    Qiao, Yu
    Xie, Weidi
    2023 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR, 2023, : 2935 - 2944
  • [38] Data Augmentation by Data Noising for Open-vocabulary Slots in Spoken Language Understanding
    Kim, Hwa-Yeon
    Roh, Yoon-Hyung
    Kim, Young-Kil
    NAACL HLT 2019: THE 2019 CONFERENCE OF THE NORTH AMERICAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: HUMAN LANGUAGE TECHNOLOGIES: PROCEEDINGS OF THE STUDENT RESEARCH WORKSHOP, 2019, : 97 - 102
  • [39] Improving Closed and Open-Vocabulary Attribute Prediction Using Transformers
    Khoi Pham
    Kafle, Kushal
    Lin, Zhe
    Ding, Zhihong
    Cohen, Scott
    Tran, Quan
    Shrivastava, Abhinav
    COMPUTER VISION, ECCV 2022, PT XXV, 2022, 13685 : 201 - 219
  • [40] PromptDet: Towards Open-Vocabulary Detection Using Uncurated Images
    Feng, Chengjian
    Zhong, Yujie
    Jie, Zequn
    Chu, Xiangxiang
    Ren, Haibing
    Wei, Xiaolin
    Xie, Weidi
    Ma, Lin
    COMPUTER VISION, ECCV 2022, PT IX, 2022, 13669 : 701 - 717