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English-to-Chinese Transliteration with Phonetic Back-transliteration

arXiv 2112.10321 ↗First posted 20 Dec 2021cs.CL cs.AIcited by 0

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Abstract (arXiv)

Transliteration is a task of translating named entities from a language to another, based on phonetic similarity. The task has embraced deep learning approaches in recent years, yet, most ignore the phonetic features of the involved languages. In this work, we incorporate phonetic information into neural networks in two ways: we synthesize extra data using forward and back-translation but in a phonetic manner; and we pre-train models on a phonetic task before learning transliteration. Our experiments include three language pairs and six directions, namely English to and from Chinese, Hebrew and Thai. Results indicate that our proposed approach brings benefits to the model and achieves better or similar performance when compared to state of the art.

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References · 5

  1. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,530
  2. 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,341
  3. 2015Scheduled Sampling for Sequence Prediction with Recurrent Neural Networkscited by 779
  4. 2017Neural Machine Translation and Sequence-to-sequence Models: A Tutorialcited by 25
  5. 2016Sequence-to-sequence neural network models for transliterationcited by 7

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