• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.229-236
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• 2011

In this paper we present light weighted English-to-Korean and Korean-to-English mobile translators on smart phones. For natural translation and higher translation quality, translation engines are hybridized with Translation Memory (TM) and Rule-based translation engine. In order to maximize the usability of the system, we combined an Optical Character Recognition (OCR) engine and Text-to-Speech (TTS) engine as a Front-End and Back-end of the mobile translators. With the BLEU and NIST evaluation metrics, the experimental results show our E-K and K-E mobile translation equality reach 72.4% and 77.7% of Google translators, respectively. This shows the quality of our mobile translators almost reaches the that of server-based machine translation to show its commercial usefulness.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.191-199
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• 2009

In this paper we present a light weighted robust Korean morphological analyzer for mobile devices such as mobile phones, smart phones, and PDA phones. Such mobile devices are not suitable for natural language interfaces for their low CPU performance and memory restriction. In order to overcome the difficulties we propose 1) an online analysis by using Key Event Handler mechanism, 2) and a robust analysis of the Korean sentences with spacing errors without its correction pre-processing. We adapt the proposed Korean analyzer to a Korean-English mobile translator, which shows 5.8% memory usage reduction and 19.0% enhancement of average response time.