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Systematic review of spell-checkers for highly inflectional languages

  • Shashank SinghEmail author
  • Shailendra Singh
Article
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Abstract

Performance of any word processor, search engine, social media relies heavily on the spell-checkers, grammar checkers etc. Spell-checkers are the language tools which break down the text to check the spelling errors. It cautions the user if there is any unintentional misspelling occurred in the text. In the area of spell-checking, we still lack an exhaustive study that covers aspects like strengths, limitations, handled errors, performance along with the evaluation parameters. In literature, spell-checkers for different languages are available and each one possesses similar characteristics however, have a different design. This study follows the guidelines of systematic literature review and applies it to the field of spell-checking. The steps of the systematic review are employed on 130 selected articles published in leading journals, premier conferences and workshops in the field of spell-checking of different inflectional languages. These steps include framing of the research questions, selection of research articles, inclusion/exclusion criteria and the extraction of the relevant information from the selected research articles. The literature about spell-checking is divided into key sub-areas according to the languages. Each sub-area is then described based on the technique being used. In this study, various articles are analyzed on certain criteria to reach the conclusion. This article suggests how the techniques from the other domains like morphology, part-of-speech, chunking, stemming, hash-table etc. can be used in development of spell-checkers. It also highlights the major challenges faced by researchers along with the future area of research in the field of spell-checking.

Keywords

Spelling Spell-check Non-word errors Real-word errors Dictionary lookup Edit-distance Recurrent neural network (RNN) 

Abbreviations

FSM

Finite state machine

DLM

Dictionary lookup method

MA

Morphological analysis

ED

Edit distance

MED

Minimum edit distance

US

Unicode splitting

cbLSTM

Character-based longest short term memory

SM

Soundex method

LED

Levenstein edit distance

CS

Confusion set

rMED

Reverse minimum edit distance

DDLM

Direct dictionary lookup method

EDM

Edit distance method

PEM

Phonetic encoding method

FSR

Finite state representation

STM

State table method

FSA

Finite state automata

PAMC

Partition around medoid clustering

DMEE

Double metaphone encoding

WF

Word frequency

S&SS

Sound and shape similarity

rEDM

Reverse edit distance method

HT

Hash table

TBA

Tree-based algorithm

POS

Parts of speech

HMM

Hidden Markov model

GUI

Graphical user interface

FST

Finite state transition

UWH

Unknown word handling

UPH

Unknown proper noun handling

POS

Parts of speech

API

Application programming interface

CW

Constituent word

MBLP

Memory based language model

FSTM

Finite state transition model

DA

Dictionary approach

CC

Canti check

CSO

Crowd sourcing

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Notes

Acknowledgements

The authors thank the reviewers for their insightful comments. The authors would also like to thank Ministry of Electronics and IT, Government of INDIA, for providing fellowship under Grant Number: PhD-MLA-4 (69)/2015-16 (Visvesvaraya PhD Scheme for Electronics and IT) to pursue Ph.D. work.

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Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringPunjab Engineering College (Deemed to be University)ChandigarhIndia

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