This paper describes a machine learning algorithm for Gujarati Part of Speech Tagging. The machine learning part is performed using a CRF model. The features given to CRF are properly chosen keeping the linguistic aspect of Gujarati in mind.
In this paper we discuss the significance of representation of images for face verification.We consider three different representations, namely, edge gradient, edge orientation and potential field derived from the edge gradient. These representations are examined in the context of face verification using a specific type of correlation filter, called the minimum average correlation energy (MACE) filter.
In this letter, we address the issue of determining the number of speakers from multispeaker speech signals collected simultaneously using a pair of spatially separated microphones. The spatial separation of the microphones results in time delay of arrival of speech signals from a given speaker.
Added on November 11, 2010
Product Type : Research Paper
License Type : Freeware
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Author : R. Kumara Swamy, K. Sri Rama Murty, B. Yegnanarayana