Tigrigna language spellchecker and correction system for mobile phone devices

This paper presents on the implementation of spellchecker and corrector system in mobile phone devices, such as a smartphone for the low-resourced Tigrigna language. Designing and developing a spell checking for Tigrigna language is a challenging task. Tigrigna script has more than 32 base letters with seven vowels each. Every first letter has six suffixes. Word formation in Tigrigna depends mainly on root-and-pattern morphology and exhibits prefixes, suffixes, and infixes. A few project have been done on Tigrigna spellchecker on desktop application and the nature of Ethiopic characters. However, in this work we have proposed a systems modeling for Tigrigna language spellchecker, detecting and correction: a corpus of 430,379 Tigrigna words has been used. To indication the validity of the spellchecker and corrector model and algorithm designed, a prototype is developed. The experiment is tested and accuracy of the prototype for Tigrigna spellchecker and correction system for mobile phone devices achieved 92%. This experiment result shows clearly that the system model is efficient in spellchecking and correcting relevant suggested correct words and reduces the misspelled input words for writing Tigrigna words on mobile phone devices

The construction of Tigrigna Spelling Checker and Corrector in android smart phones through prototyping process model

The Construction of Tigrigna Spelling Checker and Corrector in Android Smart Phones Through Prototyping Process Model is the process of developing a prototype for detecting the misspelled words and correcting them in a paragraph. The prototyping Model follows a process of Requirements gathering and analysis, Quick design, Build prototype, User evaluation, Refining prototype, Engineering the product. based on the prototyping process model step the Application will be finalized to the Tigrigna language users.The researchers used an algorithm dictionary lookup for detection of misspelled words, and Edit Distance approach to generate the valid suggestions for the misspelled words and use linguistic features of the Tigrigna language. The frequency of each word, provides a rank to each word in the list of found words to the system. Words with highest frequency will get highest rank. To show the validity of the spelling checker model and the algorithm designed, experiment was also conducted to measure the accuracy of the Prototype spelling checker and suitability of the system based on ISO 9241 usability engineering standards. Therefore, the researchers concluded based on 90.25% correction accuracy that the Model is effective in checking and correcting Tigrigna words.Keywords: Spelling, checker, proto, type, model, Algorithm, Corrector Android, Phone