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A Wavelet and Filter Bank Framework for Phonetic Classification.
Noise Robust Phonetic Classification with Linear Regularized Least Squares and Second-Order Features.
Hierarchical Large-Margin Gaussian Mixture Models for Phonetic Classification.
In this paper we present a hierarchical large-margin Gaussian mixture modeling framework and evaluate it on the task of phonetic classification. A two-stage hierarchical classifier is trained by alter...
We perform phonetic classiſcation with an architecture whose elements are binary classiſers trained via linear regularized least squares (RLS). RLS is a simple yet powerful regularization al...
Although wavelet analysis has been proposed for speech processing as an alternative to Fourier analysis, most approaches make use of off-the-shelf wavelets and dyadic tree-structured filter banks. In ...
In this paper, we present a wavelet and filter bank framework for context-independent phonetic classification with the aim of extending the work towards a full speech recognition system. The framework...
In this paper we describe our recent efforts to improve acousticphonetic modeling by developing sets of heterogeneous, phoneclass-specific measurements, and combining these diverse measurements into a...

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