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Multi-pronounciation dictionary construction for Mandarin-English bilingual phrase speech recognition system

机译:普通话 - 英语双语短语语音识别系统的多语文字典构建

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摘要

Generally, in multi-lingual communities, non-native speakers may produce speech sound which is either part of their own native language or established via merging characteristics of native pronunciation with non-native pronunciation. Recently, a Two-pass phone clustering based on Confusion Matrix (TCM) approach has been proposed to address the one-to-one phone mappings between Chinese syllables and English phones using standard Chinese and English data. In this paper, we extend TCM to the one-to-many phone mappings issue since there is the merging phenomenon of native and non-native pronunciation in bilingual speeches. Employing a knowledge-based phone set to TCM as supplements for phone clustering, a novel method termed as the TCM with Initialization and Updating of the Phone Set method (TCM-IUPS). As a result, the pronunciation dictionary is built via using the information learned by our proposed TCM-IUPS as well as canonical pronunciation. Experiments show that, compared with TCM, the Phrase Error Rate (PhrER) of TCM-IUPS is reduced by 5.27% in bilingual testing corpora and 26.09% in mono-English testing corpora compared with TCM, while the same performance is maintained in mono-Mandarin testing corpora.
机译:通常,在多语言社区中,非母语扬声器可以产生语音声音,这是他们自己的母语的一部分,或者通过与非本机发音的原生发音的合并特征建立。最近,已经提出了一种基于混淆矩阵(TCM)方法的双手电话聚类,以解决使用标准中文和英文数据的中文音节和英语电话之间的一对一手机映射。在本文中,我们将中医扩展到一对多手机映射问题,因为双语演讲的原生和非原生发音合并现象。使用基于知识的电话设置为TCM作为手机群集的补充剂,该方法称为TCM,具有电话集方法(TCM-IUP)的初始化和更新。结果,发音词典是通过使用我们提出的TCM-IUPS以及规范发音学到的信息构建的。实验表明,与TCM相比,TCM-IUP的短语错误率(短语)在双语测试中减少了5.27%,与TCM相比单音测试中的26.09%,而同时在单通剧中保持相同的表现普通话测试Corpora。

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