We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process ...
This paper presents the Croatian context-dependent acoustic modelling used in speech recognition and in speech synthesis. The proposed acoustic model is based on context-dependent ...
Sanda Martincic-Ipsic, Slobodan Ribaric, Ivo Ipsic
This study revisits the face-to-tongue articulatory inversion problem in speech. We compare the Multi Linear Regression method (MLR) with two more sophisticated methods based on H...
We investigate incremental word learning with few training examples in a Hidden Markov Model (HMM) framework suitable for an interactive learning scenario with little prior knowle...
Automatic segmentation and classification of recorded meetings provides a basis towards understanding the content of a meeting. It enables effective browsing and querying in a me...