Seliz G. Karadogan

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In this paper, we represent a new approach for robust speaker independent ASR using binary masks as feature vectors. This method is evaluated on an isolated digit database, TIDIGIT in three noisy environments (car,bottle and cafe noise types taken from DRCD Sound Effects Library). Discrete Hidden Markov Model is used for the recognition and the observation(More)
In this paper, we present a new evaluation approach for missing data techniques (MDTs) where the efficiency of those are investigated using listwise deletion method as reference. We experiment on classification problems and calculate misclassification rates (MR) for different missing data percentages (MDP) using a missing completely at random (MCAR) scheme.(More)
—The recognition of affect in speech has attracted a lot of interest recently; especially in the area of cognitive and computer sciences. Most of the previous studies focused on the recognition of basic emotions (such as happiness, sadness and anger) using categorical approach. Recently, the focus has been shifting towards dimensional affect recognition(More)
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