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A Dataset and a Novel Neural Approach for Optical Gregg Shorthand Recognition

  • Fangzhou Zhai
  • Yue Fan
  • Tejaswani Verma
  • Rupali Sinha
  • Dietrich Klakow
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11107)

Abstract

Gregg shorthand is the most popular form of pen stenography in the United States. It has been adapted for many other languages. In order to substantially explore the potentialities of performing optical recognition of Gregg shorthand, we develop and present Gregg-1916, a dataset that comprises Gregg shorthand scripts of about 16 thousand common English words. In addition, we present a novel architecture for shorthand recognition which exhibits promising performance and opens up the path for various further directions.

Keywords

Optical Gregg shorthand recognition Character recognition Convolutional neural networks Recurrent neural networks 

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Fangzhou Zhai
    • 1
  • Yue Fan
    • 1
  • Tejaswani Verma
    • 1
  • Rupali Sinha
    • 1
  • Dietrich Klakow
    • 1
  1. 1.Spoken Language Systems, Saarland Informatics CampusSaarbrückenGermany

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