@inproceedings{1315a3d841e447b0b101463f30ea98c9,
title = "On-Device Neural Language Model based Word Prediction",
abstract = "Recent developments in deep learning with application to language modeling have led to success in tasks of text processing, summarizing and machine translation. However, deploying huge language models on mobile devices for on-device keyboards poses computation as a bottle-neck due to their puny computation capacities. In this work, we propose an on-device neural language model based word prediction method that optimizes run-time memory and also provides a real-time prediction environment. Our model size is 7.40MB and has average prediction time of 6.47 ms. The proposed model outperforms existing methods for word prediction in terms of keystroke savings and word prediction rate and has been successfully commercialized.",
author = "Seunghak Yu and Nilesh Kulkarni and Haejun Lee and Jihie Kim",
note = "Publisher Copyright: {\textcopyright} COLING 2018.All right reserved.; 27th International Conference on Computational Linguistics, COLING 2018 ; Conference date: 20-08-2018 Through 26-08-2018",
year = "2018",
language = "English",
series = "COLING 2018 - 27th International Conference on Computational Linguistics, Proceedings of System Demonstrations",
publisher = "Association for Computational Linguistics (ACL)",
pages = "128--131",
booktitle = "COLING 2018 - 27th International Conference on Computational Linguistics, Proceedings of System Demonstrations",
address = "United States",
}