Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/7272
Title: A robust to outliers Hidden Markov model with application in text-dependent speaker identification
Authors: Varvarigou, Theodora 
Chatzis, Sotirios P. 
Varvarigou, Theodora 
Keywords: Computing & Processing (Hardware/Software);Communication, Networking & Broadcasting;Signal processing;Gaussian processes;Markov processes;Speakers;Speech;Pattern recognition
Issue Date: 2007
Publisher: IEEE Xplore
Source: ICSPC 2007. IEEE international conference on signal processing and communications, 2007, Pages 804-807
Abstract: Hidden Markov models using Gaussian mixture models as their hidden state distributions have been successfully applied in text-dependent speaker identification applications. Nevertheless, it is well-known that Gaussian mixture models are very vulnerable to the presence of outliers in the fitting set used for their estimation. Student's-t mixture models have been proposed recently as a heavy-tailed, tolerant to outliers alternative to Gaussian mixture models. In this paper we exploit the robustness of Student's-t mixture models in the context of hidden Markov models by introducing a new hidden Markov chain model where the hidden state distributions are Student' s-t mixture models. We experimentally show that our model outperforms competing text-dependent speaker identification techniques
URI: http://ktisis.cut.ac.cy/handle/10488/7272
ISBN: 978-1-4244-1235-8 (print)
ISSN: 978-1-4244-1236-5 (online)
10.1109/ICSPC.2007.4728441
10.1109/ICSPC.2007.4728441
10.1109/ICSPC.2007.4728441
DOI: 10.1109/ICSPC.2007.4728441
Rights: © 2007 IEEE
Type: Conference Papers
Appears in Collections:Κεφάλαια βιβλίων/Book chapters

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