An evidence theoretic classification method is proposed in this paper. In order to classify a pattern we consider its neighbours, which are taken as parts of a single source of ev...
In this paper we propose a novel general framework for unsupervised model adaptation. Our method is based on entropy which has been used previously as a regularizer in semi-superv...
Ariya Rastrow, Frederick Jelinek, Abhinav Sethy, B...
This paper takes phonetic information into account for data alignment in text-independent voice conversion. Hidden Markov Models are used for representing the phonetic structure o...
Meng Zhang, Jiaohua Tao, Jani Nurminen, Jilei Tian...
In this paper, we study the image interpolation from the game theoretic perspective and formulate the image interpolation problem as an evolutionary game. In this evolutionary gam...
We present a mixture model based approach for learning individualized behavior models for the Web users. We investigate the use of maximum entropy and Markov mixture models for ge...