This paper offers a gentle introduction to probability for linguists, assuming little or no background beyond what one learns in high school. The most important points that we emphasize are: the conceptual difference between probability and frequency, the use of maximizing probability of an observation by considering different models, and Kullback-Leibler divergence. Nous offrons une introducti...

Recent Automatic Speech Recognition (ASR) studies have shown that Kullback-Leibler diverge based hidden Markov models (KL-HMMs) are very powerful when only small amounts of training data are available. However, since the KL-HMMs use a cost function that is based on the Kullback-Leibler divergence (instead of maximum likelihood), standard ASR algorithms such as the commonly used decision tree cl...

In this paper, by conditioning on the matrix variate normal distribution (MVND) the construction of the matrix t-type family is considered, thus providing a new perspective of this family. Some important statistical characteristics are given. The presented t-type family is an extension to the work of Dickey [8]. A Bayes estimator for the column covariance matrix &Sigma of MVND is derived under ...

This paper addresses the question of clustering density curves around a unit circle by approximating each such curve mixture an appropriate number von Mises distributions. is done first defining distance between any two either via $$L^2$$ or symmetrized Kullback–Leibler divergence. We show that both these measures yield similar results. After demonstrating simulations proposed methods work succ...

In this paper identification of laryngeal disorders using cepstral parameters of human voice is researched. Mel-frequency cepstral coefficients (MFCCs), extracted from audio recordings of patient’s voice, are further approximated, using various strategies (sampling, averaging, and clustering by Gaussian mixture model). The effectiveness of similarity-based classification techniques in categoriz...

We analyze a contrasting dynamical behavior of Gibbs–Shannon and conditional Kullback-Leibler entropies, induced by time-evolution of continuous probability distributions. The question of predominantly purposedependent entropy definition for non-equilibriummodel systems is addressed. The conditional Kullback–Leibler entropy is often believed to properly capture physical features of an asymptoti...