SPECIL: Spell Error Corpus for the Indonesian Language - Yanfi Yanfi; Reina Setiawan; Haryono Soeparno; Widodo Budiharto (IEEE Access, 2023)
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.