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In emotion classification of speech signals, the popular features employed are statistics of fundamental frequency, energy contour, duration of silence and voice quality. However, the performance of systems employing these features degrades substantially when more than two categories of emotion are to be classified. In this paper, a text independent method(More)
Snakes, or active contour models, have been widely used in image segmentation. However, most present snake models do not discern between positive and negative step edges. In this paper, a new type of dynamic external force for snakes named dynamic directional gradient vector flow (DDGVF) is proposed that uses this information for better performance. It(More)
In this paper, an automated method of boundary detection of the left ventricle (LV) is proposed. The method uses a watershed transform and morphological operation to locate the region containing the LV, then performs snake deformation with a multiscale directional edge map for the detection of the endocardial boundary of the LV
In this paper, three systems for classification of stress in speech are proposed. The first system makes use of linear short time Log Frequency Power Coefficients (LFPC), the second employs Teager Energy Operator (TEO) based Nonlinear Frequency Domain LFPC features (NFD-LFPC) and the third uses TEO based Nonlinear Time Domain LFPC features (NTD-LFPC). The(More)
Hidden Markov model (HMM) has been a popular mathematical approach for sequence classification such as speech recognition since 1980s. In this paper, a novel two-channel training strategy is proposed for discriminative training of HMM. For the proposed training strategy, a novel separable-distance function that measures the difference between a pair of(More)
In the detection of the boundary of the left ventricle from echocardiographic images, the crucial step is to determine the region of interest (ROI) or the center point (CP) of the left ventricle. In this paper, a new algorithm is proposed for automatic detection of the ROI and CP of the left ventricle from echocardiographic images. The method makes use of(More)
In this paper, a novel approach for speaker recognition is proposed. The approach makes use of adaptive boosting (AdaBoost) and C4.5 decision trees for closed set, text-dependent speaker recognition. A subset of 20 speakers, 10 male and 10 female, drawn from the YOHO speaker verification corpus is used to assess the performance of the system. Results reveal(More)