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In this paper we present a method for identification of temporal patterns that are predictive of events in a dynamic data system. The proposed new MRPS-HMM method applies a hybrid model using Reconstructed Phase Space (RPS) and stochastic state estimation via Hidden Markov Model (HMM) to search predictive patterns. This method constructs a multivariate phase space by embedding each data sequence with...
This paper presents a mispronunciation detection system which uses automatic speech recognition to effectively detect the phone-level mispronunciations in the Cantonese learners of English. Our approach extends a target pronunciation lexicon with possible phonetic confusions that may lead to pronunciation errors to generate an extended pronunciation lexicon that contains both target pronunciations...
This paper presents a method using speech recognition with linguistic constraints to detect the mispronunciations made by Cantonese learners of English. The predicted pronunciation errors have been derived from cross-language phonological comparisons, which are used to generate the erroneous pronunciation variations in a lexicon. The acoustic models are trained with native speakerspsila speech and...
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