使用上下文信息PB-SMT的英语-印地语音译:NEWS 2009的DCU系统

Rejwanul Haque, Sandipan Dandapat, Ankit K. Srivastava, S. Naskar, Andy Way
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引用次数: 33

摘要

本文介绍了NEWS 2009机器音译共享任务中的英语-北印度语音译,将源上下文建模添加到最先进的基于对数线性短语的统计机器翻译(PB-SMT)中。源上下文特征使我们能够利用源相似性和目标相似性,正如语言模型所建模的那样。我们使用基于内存的分类框架,在避免数据稀疏问题的同时有效地估计这些特征。我们在字符和音译单位(TU)水平上进行了实验。位置相关的源上下文特性在所有评估度量方面产生了显著的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
English-Hindi Transliteration Using Context-Informed PB-SMT: the DCU System for NEWS 2009
This paper presents English---Hindi transliteration in the NEWS 2009 Machine Transliteration Shared Task adding source context modeling into state-of-the-art log-linear phrase-based statistical machine translation (PB-SMT). Source context features enable us to exploit source similarity in addition to target similarity, as modelled by the language model. We use a memory-based classification framework that enables efficient estimation of these features while avoiding data sparseness problems.We carried out experiments both at character and transliteration unit (TU) level. Position-dependent source context features produce significant improvements in terms of all evaluation metrics.
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