Segmentation and recognition of phonetic features in handwritten Pitman shorthand

Ma, Yukun; Leedham, Graham; Higgins, Colin; Htwe, Swe Myo

doi:10.1016/j.patcog.2007.10.014

Cited by 6 publications

(2 citation statements)

References 17 publications

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“…Examples of these methods are Unistrokes [7] and Graffiti [2]. As for shorthand, it allows users to reach high performances in terms of speed (up to 100 WPM [15]). Nevertheless it appears unlikely that common users could adopt such a difficult to learn method.…”

Section: Text Entry Methods: a Brief Surveymentioning

confidence: 99%

Text entry with KeyScretch

Costagliola

Fuccella

Capua³

2011

Proceedings of the 16th International Conference on Intelligent User Interfaces

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KeyScretch is a recently proposed text entry method which makes use of gestures to input frequent word chunks on a menu-augmented soft keyboard. Each gesture is initiated on a key and is driven by the key surrounding menu. In this paper we present the performance of an instance of the method with a 4-items menu, specifically designed for the Italian language. The study shows that the method is easy to learn and significantly outperforms the traditional tappingbased method on the QWERTY layout. Author Keywords

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Section: Text Entry Methods: a Brief Surveymentioning

confidence: 99%

Text entry with KeyScretch

Costagliola

Fuccella

Capua³

2011

Proceedings of the 16th International Conference on Intelligent User Interfaces

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“…Yang Ma et al [3] presented a recognition system for PSL which includes the followings four major procedures: segmenting and classifying consonant outlines; classifying vowels and diphthong symbols according to their shape characteristics; classifying shortforms with Hausdorff distance; and dealing with the problem of smooth junction with a new machine compatible shorthand. An experiment on 461 outlines each containing one sooth junction shows that the recognition rate achieved was 93.41%.…”

Section: Related Workmentioning

confidence: 99%

A Neural Network based Method for Recognition of Handwritten English Pitman's Shorthand

Mishra¹,

Alam²

2014

IJCA

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Pitman Shorthand method of documenting is normally practiced by stenographers to take dictation at speaking speed invented by Sir Isaac Pitman in 1837. Special graphical symbols are used in this method of representing phonetic compositions of the dictated text for certain interval. This shorthand representation itself is a compressed and encrypted format of the English text. The Pitman Shorthand Language (PSL) has the practical advantage of high speed of recording, more than 120-200 words per minute, because of which it is universally acknowledged. This recording medium has its continued existence in spite of considerable developments in speech processing systems, which are not universally established yet. In this method of documenting, speech is directly converted into phonetic strokes, where each phonetic stroke is a composition of consonants and vowels. These consonants are called consonant primitives or simply primitives. In order to exploit the vast transcribing potential of PSL a new area of research on automation of PSL processing is conceived. In this work, the Neural Network Classifier for recognition of PSL at word level is presented. All the activities such as preprocessing of data (image cropping, resizing and implementations) have been carried out using MATLAB. As per this experiment, 94% recognition accuracy is achieved.

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

Zhai

Fan

Verma

et al. 2018

Text, Speech, and Dialogue

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Segmentation and recognition of phonetic features in handwritten Pitman shorthand

Cited by 6 publications

References 17 publications

Text entry with KeyScretch

Text entry with KeyScretch

A Neural Network based Method for Recognition of Handwritten English Pitman's Shorthand

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

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Segmentation and recognition of phonetic features in handwritten Pitman shorthand

Cited by 6 publications

References 17 publications

Text entry with KeyScretch

Text entry with KeyScretch

A Neural Network based Method for Recognition of Handwritten English Pitman&apos;s Shorthand

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

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A Neural Network based Method for Recognition of Handwritten English Pitman's Shorthand