Deep learning based spell checker for Malayalam language.
Saved in:
| Title: | Deep learning based spell checker for Malayalam language. |
|---|---|
| Authors: | Sooraj, S.1 sudhakar.sooraj@gmail.com, Manjusha, K.1, Anand Kumar, M.1, Soman, K.P.1, Thampi, El-Alfy, Mitra, Trajkovic |
| Source: | Journal of Intelligent & Fuzzy Systems. 2018, Vol. 34 Issue 3, p1427-1434. 8p. |
| Subjects: | Deep learning, Spell checkers (Computer programs), Malayalam language, English language, Error correction (Information theory) |
| Abstract: | Spell checking plays an important role in conveying correct information and hence helps in clear communication. Spell checkers for English language are well established. But in case of Indian languages, especially Malayalam lacks a well developed spell checker. The spell checkers that currently exist for Indian languages are based on traditional approaches such as rule based or dictionary based. The rich morphological nature of Malayalam makes spell checking a difficult task. The proposed work is a novel attempt and first of its kind that focuses on implementing a spell checker for Malayalam using deep learning. The spell checker comprises of two processes: error detection and error correction. The error detection section employs a LSTM based neural network which is trained to identify the misspelled words and the position where the error has occurred. The error detection accuracy is measured using the F1 score. Error correction is achieved by the selecting the most probable word from the candidate word suggestions. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Intelligent & Fuzzy Systems is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | Spell checking plays an important role in conveying correct information and hence helps in clear communication. Spell checkers for English language are well established. But in case of Indian languages, especially Malayalam lacks a well developed spell checker. The spell checkers that currently exist for Indian languages are based on traditional approaches such as rule based or dictionary based. The rich morphological nature of Malayalam makes spell checking a difficult task. The proposed work is a novel attempt and first of its kind that focuses on implementing a spell checker for Malayalam using deep learning. The spell checker comprises of two processes: error detection and error correction. The error detection section employs a LSTM based neural network which is trained to identify the misspelled words and the position where the error has occurred. The error detection accuracy is measured using the F1 score. Error correction is achieved by the selecting the most probable word from the candidate word suggestions. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 10641246 |
| DOI: | 10.3233/JIFS-169438 |
