DOI: 10.18178/wcse.2021.02.012
Neural Named Entity Transliteration for Myanmar to English Language Pair
Abstract— Named entity (NE) transliteration is mainly a phonetically based transcription of names across languages using different writing systems. This is a crucial task for various downstream natural language processing applications, such as information retrieval, machine translation, automatic speech recognition and so on. Robust transliteration of named entities is still a challenging task for Myanmar language because of the complex writing system and the lack of data. In this paper, we proposed our Myanmar-English named entity terminology dictionary and experimented on transformer-based neural network model. Furthermore, we evaluated the performance of neural network-based approach on the transliteration tasks using BLEU score. Different units in the Myanmar script, i.e., character units, sub-syllable units and syllables units are compared in the experiments.
Index Terms— myanmar language, transformer, neural network, named entity, transliteration
Aye Myat Mon, Khin Mar Soe
University of Computer Studies, Yangon, MYANMAR
Cite: Aye Myat Mon, Khin Mar Soei, "Neural Named Entity Transliteration for Myanmar to English Language Pair, " Proceedings of 2021 the 11th International Workshop on Computer Science and Engineering (WCSE 2021), pp. 70-74, February 25-27, 2021.