Simon Ka-Lung Ho

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PLASER is a multimedia tool with instant feedback designed to teach English pronunciation for high-school students of Hong Kong whose mother tongue is Cantonese Chinese. The objective is to teach correct pronunciation and not to assess a student's overall pronunciation quality. Major challenges related to speech recognition technology include: allowance for(More)
Eigenvoice-based methods have been shown to be effective for fast speaker adaptation when only a small amount of adaptation data, say, less than 10 s, is available. At the heart of the method is principal component analysis (PCA) employed to find the most important eigenvoices. In this paper, we postulate that nonlinear PCA using kernel methods may be even(More)
Eigenvoice-based methods have been shown to be effective for fast speaker adaptation when the amount of adaptation data is small, say, less than 10 seconds. In traditional eigenvoice (EV) speaker adaptation, linear principal component analysis (PCA) is used to derive the eigenvoices. Recently, we proposed that eigenvoices found by nonlinear kernel PCA could(More)
Recently, we proposed an improvement to the conventional eigenvoice (EV) speaker adaptation using kernel methods. In our novel kernel eigenvoice (KEV) speaker adaptation, speaker supervectors are mapped to a kernel-induced high dimensional feature space, where eigenvoices are computed using kernel principal component analysis. A new speaker model is then(More)
Eigenvoice speaker adaptation has been shown to be effective when only a small amount of adaptation data is available. At the heart of the method is principal component analysis (PCA) employed to find the most important eigenvoices. In this paper, we postulate that nonlinear PCA, in particular kernel PCA, may be even more effective. One major challenge is(More)
Recently, we proposed an improvement to the eigenvoice (EV) speaker adaptation called kernel eigenvoice (KEV) speaker adaptation. In KEV adaptation, eigenvoices are computed using kernel PCA, and a new speaker's adapted model is implicitly computed in the kernel-induced feature space. Due to many on-line kernel evaluations, both adaptation and subsequent(More)
Recently, we proposed two improvements to the eigenvoice (EV) speaker adaptation using kernel methods: kernel eigenvoice (KEV) speaker adaptation, and embedded kernel eigenvoice (eKEV) speaker adaptation. In both KEV and eKEV adaptation methods, kernel eigenvoices are computed using kernel PCA, and an implicit speaker adapted model is defined as a linear(More)
Verification problems are usually posted as a 2-class problem and the objective is to verify if an observation belongs to a class, say, A or its complement A'. However , we find that in a computer-assisted language learning application, because of the relatively low reliability of phoneme verification — with an equal-error-rate of more than 30% — a system(More)
ii I hereby declare that I am the sole author of this thesis. I authorize the University of Waterloo to lend this thesis to other institutions or individuals for the purpose of scholarly research. I further authorize the University of Waterloo to reproduce this thesis by photocopying or by other means, in total or in part, at the request of other(More)
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