Prashanth Gurunath Shivakumar

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We propose a simplified and supervised i-vector modeling scheme for the speaker age regression task. The supervised i-vector is obtained by concatenating the label vector and the linear regression matrix at the end of the mean super-vector and the i-vector factor loading matrix, respectively. Different label vector designs are proposed to increase the(More)
Developing a robust Automatic Speech Recognition (ASR) system for children is a challenging task because of increased variability in acoustic and linguistic correlates as function of young age. The acoustic variability is mainly due to the developmental changes associated with vocal tract growth. On the linguistic side, the variability is associated with(More)
Automatic classification of depression using audiovisual cues can help towards its objective diagnosis. In this paper, we present a multimodal depression classification system as a part of the 2016 Audio/Visual Emotion Challenge and Workshop (AVEC2016). We investigate a number of audio and video features for classification with different fusion techniques(More)
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