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Speaker adapted dynamic lexicons containing phonetic deviations of words

Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2009年第10期10卷 1461-1475页

作者： Bahram VAZIRNEZHAD Farshad ALMASGANJ Seyed Mohammad AHADI Ari CHANEN Biomedical Engineering Department Amirkabir University of Technology Language and Knowledge Management Research Lab School of Information TechnologiesUniversity of Sydney Electrical Engineering Department Amirkabir University of Technology

Speaker variability is an important source of speech variations which makes continuous speech recognition a difficult *** automatic speech recognition(ASR) models to the speaker variations is a well-known strategy to cope with the *** all such techniques focus on developing adaptation solutions within the acoustic models of the ASR *** variations of the acoustic features constitute an important portion of the inter-speaker variations,they do not cover variations at the phonetic *** variations are known to form an important part of variations which are influenced by both micro-segmental and suprasegmental ***-speaker phonetic variations are influenced by the structure and anatomy of a speaker's articulatory system and also his/her speaking style which is driven by many speaker background characteristics such as accent,gender,age,socioeconomic and educational *** effect of inter-speaker variations in the feature space may cause explicit phone recognition *** errors can be compensated later by having appropriate pronunciation variants for the lexicon entries which consider likely phone misclassifications besides *** this paper,we introduce speaker adaptive dynamic pronunciation models,which generate different lexicons for various speaker clusters and different ranges of speech *** models are hybrids of speaker adapted contextual rules and dynamic generalized decision trees,which take into account word phonological structures,rate of speech,unigram probabilities and stress to generate pronunciation variants of *** the set of speaker adapted dynamic lexicons in a Farsi(Persian) continuous speech recognition task results in word error rate reductions of as much as 10.1% in a speaker-dependent scenario and 7.4% in a speaker-independent scenario.

关键词： Pronunciation models Continuous speech recognition lexicon adaptation

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