Open AccessAgglutinative Language Speech Recognition Using Automatic Allophone Deriving
Author(s) -
Xu Ji,
Pan Jielin,
Yan Yonghong
Publication year - 2016
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2016.03.020
Subject(s) - agglutinative language , pronunciation , computer science , vocabulary , artificial intelligence , natural language processing , speech recognition , linguistics , philosophy , morpheme
Agglutinative language involves agglutination extensively, which results in the significant pronunciation variations in different contexts. Therefore, it is a problem to use phoneme sets translated from their written forms as basic units for acoustic modeling, due to the incapability to capture the pronunciation variations in Large‐vocabulary continuous speech recognition (LVCSR). This paper presented a novel approach called Automatic allophone deriving (AAD) to create allophone candidates without any linguistic prior knowledge. Furthermore, an enhanced approach AAD‐LT is proposed in which longtime features are used in AAD approach. Experiments are conducted on three languages which contains two agglutinative ones and an analytic one. The experiments suggest that AAD Long‐time (AAD‐LT) is very effective for the agglutinative languages in which more than 10% relative CER reduction is obtained.