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An Image based Approach for Speech Perception

Nguyen, Quang Trung and Bui, The Duy and Ma, Thi Chau (2015) An Image based Approach for Speech Perception. In: NICS: 2nd National Foundation for Science and Technology Development Conference on Information and Computer Science, 16-18 September 2015, Ho Chi Minh city, Vietnam.

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Classification of speech signal is one of the most vital problems in speech perception and spoken word recognition. Although, there have been many studies on the classification of speech signals but the results are still limited. In this paper, we propose an image based approach for speech signal classification based on the combination of Local Naïve Bayes Nearest Neighbor (LNBNN) and Scale-invariant Feature Transform (SIFT) features. The proposed approach allows training feature vectors to have different sizes and no re-training is needed for additional training data after training phase. With this approach, achieved classification results are very satisfactory. They are 72.8, 100 and 95.0 on the ISOLET, Digits and Places databases, respectively.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Bayes methods;signal classification;speech recognition;transforms;vectors;ISOLET;LNBNN;SIFT features;digits;feature vectors;image based approach;local naive Bayes nearest neighbor;places databases;scale-invariant feature transform;speech perception;speech signal classification;spoken word recognition;training data;training phase;Databases;Feature extraction;Hidden Markov models;Mel frequency cepstral coefficient;Speech;Speech recognition;Training;lnbnn;sift;speech classification;speech perception
Subjects: Information Technology (IT)
Divisions: Faculty of Information Technology (FIT)
Depositing User: Prof. Xuan-Tu Tran
Date Deposited: 28 Dec 2015 02:56
Last Modified: 28 Dec 2015 02:56

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