@inproceedings{qiu-zhu-2016-learning,
title = "Learning {I}ndonesian-{C}hinese Lexicon with Bilingual Word Embedding Models and Monolingual Signals",
author = "Qiu, Xinying and
Zhu, Gangqin",
editor = "Wu, Dekai and
Bhattacharyya, Pushpak",
booktitle = "Proceedings of the 6th Workshop on South and Southeast {A}sian Natural Language Processing ({WSSANLP}2016)",
month = dec,
year = "2016",
address = "Osaka, Japan",
publisher = "The COLING 2016 Organizing Committee",
url = "https://aclanthology.org/W16-3720",
pages = "188--193",
abstract = "We present a research on learning Indonesian-Chinese bilingual lexicon using monolingual word embedding and bilingual seed lexicons to build shared bilingual word embedding space. We take the first attempt to examine the impact of different monolingual signals for the choice of seed lexicons on the model performance. We found that although monolingual signals alone do not seem to outperform signals coverings all words, the significant improvement for learning word translation of the same signal types may suggest that linguistic features possess value for further study in distinguishing the semantic margins of the shared word embedding space.",
}
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%0 Conference Proceedings
%T Learning Indonesian-Chinese Lexicon with Bilingual Word Embedding Models and Monolingual Signals
%A Qiu, Xinying
%A Zhu, Gangqin
%Y Wu, Dekai
%Y Bhattacharyya, Pushpak
%S Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016)
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F qiu-zhu-2016-learning
%X We present a research on learning Indonesian-Chinese bilingual lexicon using monolingual word embedding and bilingual seed lexicons to build shared bilingual word embedding space. We take the first attempt to examine the impact of different monolingual signals for the choice of seed lexicons on the model performance. We found that although monolingual signals alone do not seem to outperform signals coverings all words, the significant improvement for learning word translation of the same signal types may suggest that linguistic features possess value for further study in distinguishing the semantic margins of the shared word embedding space.
%U https://aclanthology.org/W16-3720
%P 188-193
Markdown (Informal)
[Learning Indonesian-Chinese Lexicon with Bilingual Word Embedding Models and Monolingual Signals](https://aclanthology.org/W16-3720) (Qiu & Zhu, WSSANLP 2016)
ACL