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Solewicz Y.A.,Technology Section | Aronowitz H.,IBM
Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH | Year: 2011

This paper presents a novel self-contained two-wire speaker recognition framework. The classical approach to two-wire speaker recognition usually requires a preliminary explicit speaker segmentation stage in order to extract audio files for the two hypothesized speakers. We propose an implicit speaker segmentation method implemented at the supervector level of speaker recognition systems. By periodically extracting successive supervectors from the two-wire audio it is possible to further associate them to each of the hypothesized speakers before scoring both streams. We show that the proposed technique leads to recognition performance comparable to standard approaches while requiring substantially less resources. Copyright © 2011 ISCA.


Yifrach A.,Ben - Gurion University of the Negev | Novoselsky E.,Ben - Gurion University of the Negev | Solewicz Y.A.,Technology Section | Yitzhaky Y.,Ben - Gurion University of the Negev
Pattern Analysis and Applications | Year: 2016

The illumination variation is one of the well-known problems in face recognition under uncontrolled environments. Several techniques have been presented in the literature to cope up with this problem. Lately, a technique known as Nuisance Attribute Projection (NAP), originally developed for the speaker recognition field was introduced to image processing in order to compensate for luminance artifacts. This paper extends and improves the earlier work by exploring efficient methodologies for using NAP for face recognition under varied illumination conditions. In particular, we propose a modified NAP formulation and show that NAP training can be simplified for face recognition. Additionally, we suggested a compact framework merging between NAP compensation and eigenface recognition. A series of experiments using the extended YaleB database, and a cross-validation using the PIE CMU and the Oulo databases are performed to validate our proposals. © 2014, Springer-Verlag London.

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