文章基本信息

标题：Effects of Syllable Language Model on Distinctive Phonetic Features (DPFs) based Phoneme Recognition Performance
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作者：Huda, Mohammad Nurul ; Banik, Manoj ; Muhammad, Ghulam 等
期刊名称：Journal of Multimedia
印刷版ISSN：1796-2048
出版年度：2010
卷号：5
期号：6
页码：543-550
DOI：10.4304/jmm.5.6.543-550
语种：English
出版社：Academy Publisher
摘要：This paper presents a distinctive phonetic features (DPFs) based phoneme recognition method by incorporating syllable language models (LMs). The method comprises three stages. The first stage extracts three DPF vectors of 15 dimensions each from local features (LFs) of an input speech signal using three multilayer neural networks (MLNs). The second stage incorporates an Inhibition/Enhancement (In/En) network to obtain more categorical DPF movement and decorrelates the DPF vectors using the Gram-Schmidt orthogonalization procedure. Then, the third stage embeds acoustic models (AMs) and LMs of syllable-based subwords to output more precise phoneme strings. From the experiments, it is observed that the proposed method provides a higher phoneme correct rate as well as a tremendous improvement of phoneme accuracy. Moreover, it shows higher phoneme recognition performance at fewer mixture components in hidden Markov models (HMMs).
关键词：distinctive phonetic features; language models; syllable based subword; inhibition/enhancement