Covariance Intersection fusion is a linear rule for combining estimates. If the cross-correlation matrix of the errors of two estimates is unknown, the rule is bound-optimal. This paper elaborates the case when some elements of the cross-correlation matrix are known. Techniques for cons...

This paper describes experiments on phonetic speech segmentation of audiobooks by using LSTM neural networks. The segmentation procedure includes an iterative adaptation of an initial speaker-independent model. The experimental data involves 5 audiobooks recorded by various renowned Czech speakers. Ab...

This paper deals with identification of noise covariance matrices of a dynamic system described by a linear discrete-in-time time-invariant stochastic state-space model. In particular, the parametric identifiability of the correlations methods is analysed and explicit relations for determination of a&...

In this paper, we introduce a new Czech subjectivity dataset of 10k manually annotated subjective and objective sentences from movie reviews and descriptions. Our prime motivation is to provide a reliable dataset that can be used with the existing English dataset as a benchmark...

This paper is focused on searching the shortest paths for all departure times (profile search). This problem is called a time-dependent shortest path problem (TDSP) and is important for optimization in transportation. Particularly this paper deals with the ε-approximation of TDSP. The p...