The Fisher kernel is a generic framework which combines the benefits of generative and discriminative approaches to pattern classification. In this contribution, we propose to a...
In this paper we introduce a new embedding technique to find the linear projection that best projects labeled data samples into a new space where the performance of a Nearest Neig...
A critical issue of applying Linear Discriminant Analysis (LDA) is both the singularity and instability of the within-class scatter matrix. In practice, particularly in image recog...
We describe recent progress in the field of prosodic modeling for speaker verification. In a previous paper, we proposed a technique for modeling syllable-based prosodic feature...
Principle Component Analysis (PCA) technique is an important and well-developed area of image recognition and to date many linear discrimination methods have been put forward. Desp...