Spell Checker for the Indonesian Language: Extensive Review

IEEE Access

In this study, we present the first spell error corpus for the Indonesian Language (SPECIL). This corpus provides a comprehensive resource for researchers and practitioners to detect and correct spelling errors in Bahasa Indonesia (Indonesian). It should be emphasized that currently, there is no recognized corpus for identifying spelling mistakes in the Indonesian language that has been officially released or made accessible. This study also provides a systematic literature review to identify resources and methodologies for building a corpus for spelling error detection and correction in Indonesia. A corpus was created using a combination of manual and automatic methods. The results of this study are a review of publications relating to corpora and spelling, the novel algorithm of six types of spelling errors, and the production of a corpus comprising over 180,000 tokens in 21,500 sentences, including non-word, real-word, and punctuation errors. Using the developed corpus, various Natural Language Processing (NLP) models, including spell checkers and language models, can be trained and tested to enhance their accuracy and effectiveness in identifying and rectifying errors in Indonesian texts.Moreover, the corpus can be used to develop and evaluate new algorithms and techniques for spelling error detection and correction in Indonesia. The SPECIL corpus is publicly available and accessible.It is expected that SPECIL will inspire further research in this area and facilitate the development of more accurate and effective spelling error detection and correction tools in Indonesian language. INDEX TERMS Corpus, Indonesian language, natural language processing, spell.

Internasional Journal of Data Science, Engineering, and Anaylitics

At educational institutions, especially at University, writing scientific papers is a skill that must be possessed by academics such as educators and students. However, writing scientific papers is not easy, there are many provisions and rules that need to be fulfilled. Several studies show that there are still many academics who make mistakes in writing their scientific papers. Some of the mistakes made include punctuation errors, typographic writing errors and the use of non-standard words in Indonesian. Researchers in Indonesia have developed various spelling error detection applications in Indonesian-language scientific papers. This study tries to analyze the development of an application framework for detecting Indonesian spelling errors from various assessment indicators. This study tries to compare the application framework for detecting spelling errors between other studies with proposed application that named KEBI 1.0 Checker. KEBI 1.0 Checker as a spelling error detection ...

2014

Spellchecker is software that analyzes possible misspellings in the text. It is the process of detecting and sometimes providing some suggestions for incorrectly spelled words in a text. If dictionary of spell checker is larger than higher is the error detection and error correction rate. Though considerable work has been done in English language but not much work has been done in regional language of India including Punjabi. Punjabi world’s 12th most widely spoken language. The only available spell checker for Punjabi is AKHAR and SUDHAR. NLP (Natural language processing) is a field of computer science concerned with interaction between computer and human language. In this paper we have discussed different techniques and about different spell checker available in different Indian regional languages and study about all spell checker whose websites are available and check their efficiency through their ranking. In future we will make a Punjabi spell checker. We will combine concept o...

Lontar Komputer : Jurnal Ilmiah Teknologi Informasi, 2021

Many Indonesian spelling errors occur in research papers published to the public, closely related to academics in all institutions such as research institutions, government, schools, and universities. The spelling errors usually writing punctuation, writing letters, writing words, writing words originating from foreign or regional languages (uptake words), using affixed words, and writing ineffective sentences. The mistakes made by the academics then become a cycle in the academic environment. They usually provide guidance for writing an undergraduate thesis, thesis, dissertations to students, or the other forms of documents and scientific papers. Therefore, the research proposed the application to facilitate all authors of scientific papers in producing quality scientific works based on the General Guidelines for Indonesian Spelling published by the Agency for Development and Language Development. The application is named KEBI 1.0 Checker (Indonesian Spelling Error 1.0 Checker), a ...

Journal of Research in Science, Computing and Engineering, 2008

SpellCheF is a spell checker for Filipino that uses a hybrid approach in detecting and correcting misspelled words in a document. Its approach is composed of dictionary-lookup, n-gram analysis, Soundex and character distance measurements. It is a plug-in to OpenOffice Writer. Two spelling rules and guidelines, namely, the Komisyon sa Wikang Filipino 2001 Revision of the Alphabet and Guidelines in Spelling the Filipino Language (or KWF), and the Gabay sa Editing sa Wikang Filipino (or GABAY) rulebooks, were incorporated into the system. SpellCheF is composed of three modules, namely the lexicon builder, the detector and the corrector. These three modules used both manual-formulated and learned rules to carry out their tasks. Test results showed that the lexicon builder was able to correctly categorize words based on the spelling rules used. It also generated three databases, namely, (1) the KWF-compliant words database, (2) the Gabay-compliant words database, and (3) the database of words common to both KWF and GABAY. The detector module had an overall error rate of 7% in identifying misspellings. Furthermore, it was observed that n-gram analysis performed better than the simple dictionary look-up. The corrector module had a 94% accuracy rate in generating word suggestions. Results also showed that using the soundex code, more suggestions were generated compared to the use of n-gram analysis. However, the first character of the soundex-based suggestions was always the same are the first character of the misspelled word.

Spell checker is a program used for examining the spelling errors and also improving that faults in the text or a document. Spell checker is a platform which is used to identify the words which are misspelled and update the user about those misspelled words. It depend on the components of spell checker either to spontaneously accurate the misspelled word or ask the user to select the right word from the recommendations which are existing for that specific misspelled word. Spell checker may be an operation which has ability of functioning on a huge part of text or as an element of larger application such as text editor, email, blog writing, keyword searching. Developing a spell checker for Indian languages such as Punjabi, Hindi and Oria etc. step-up several new problems which are not faced in English, which makes the design of spell checker very challenging. The very first constraint for developing any spell checker is to have dictionary of different words of that language which will work as word list. This paper survey the different available spell checker for Indian language (Hindi and Punjabi) and their approach used to detect and correct spell errors.

2013

Spelling Correction is a process of detecting and sometimes providing suggestions for incorrectly spelled words in a text. Spell Checker is an application program that flags words in a document that may not be spelled correctly. Spell Checker may be stand-alone capable of operating on a block a text such as word processor, electronic dictionary. When some text is given as an input to spell checker, it list outs the incorrect words separately by checking their availability in the dictionary. Finally it provides the suggestions for the incorrect words from the dictionary. This survey paper covers almost all the spelling correction techniques. Keywords— Spell Checker, NLP, Error detection techniques, Error correction techniques.

2020

In the Indonesian context, students who learn English face some problems in spelling words. They often make spelling errors in essay writing. This study aims to explore and categorize spelling errors made by Indonesian secondary school students and the primary sources contributing the errors based on Error Analysis (EA) framework. The participants consisted of 38 students chosen from a secondary school in Lampung, Indonesia. The data were obtained from documentation of student’s written essays, and responses in the questionnaire analyzed based on Carney’s (1997) categories of spelling error and Richards’s (1980) types of error sources. The findings showed that errors under categories of variant, slip, and the split was the most frequently found as the students were mistaken in choosing among the competing letters and sounds and also careless with the correct spelling. Besides, the major error sources were associated with the Indonesian (L1) interference when students transferred th...

Spell-checking is the process of detecting and sometimes providing suggestions for incorrectly spelled words in a text. Spell checking system can be created with the combination of handcrafted rules by considering grammatical features of the language for which spell checking system is to be created and a dictionary which contain the accurate spellings of various words in the target language. Basically, the better the handcrafted rule and larger the dictionary of a spell-checker is, the higher is the error detection rate; otherwise, misspellings would pass undetected. Every word from the text is looked up in the speller lexicon. The system is made to check the spellings and to correct them using various techniques for Punjabi and English text. In this proposed system input in form of a paragraph is given that can include incorrect words and the system will generate the result which contain the accurate text after eliminating the errors.

2007

This paper describes an empirical study of spelling errors using a learner corpus of university-level English. The corpus, known as CALES (Corpus Archive of Learner English in Sabah/Sarawak), consists of argumentative essays collected from university students in three public universities in Sarawak and Sabah. After describing the methodology of the CALES project, the paper outlines how spelling errors can be classified, using a combination of pre-existing categories from the literature, and categories observed in the data. The data demonstrates clearly that spelling is still a major issue both for teachers and learners, and that many students make spelling errors that fit into known categories, despite the fact that they have been studying English for at least 10 years in the Malaysian education system. As well as making observations, this paper offers a number of speculations about why students make spelling errors, and proposes some recommendations of how to prevent these errors from appearing in student writing.