One problem with speech synthesis impeding high quality is the occurrence of audible discontinuities at segment boundaries. Formant jumps across concatenation points suggest the problem to be due to spectral differences. The problem is most apparent in vowels and semi-vowels. We propose to reduce the number of audible discontinuities by adding context-sensitive diphones to the database. The num...

SUMMARY In order to measure the distance between a robust function evaluated under the true regression model and under a tted model, we propose a generalized Kullback-Leibler information. Using this generalization we have developed three robust model selection criteria, AICR , AICCR and AICCR, that allow the selection of candidate models that not only t the majority of the data, but also take i...

We apply the recent theory of information processing to a hybrid distributed detection architecture that combines the traditional parallel and tandem architectures. Central to this theory is the Kullback-Leibler discrimination distance and a quantity known as the information transfer ratio, defined as the ratio of the KL distances between the distributions characterizing the input and output of...

Because of the spectral difference between speech and acoustic events, we propose using Kullback-Leibler distance to quantify the discriminant capability of all speech feature components in acoustic event detection. Based on these distances, we use AdaBoost to select a discriminant feature set and demonstrate that this feature set outperforms classical speech feature set such as MFCC in one-pas...

This paper presents a novel algorithm to build hierarchies from independent component analyzer mixtures and its application to image similarity measure. The hierarchy algorithm composes an agglomerative (bottom-up) clustering from the estimated parameters (basis vectors and bias terms) of the ICA mixture. Merging at different levels of the hierarchy is made using the Kullback-Leibler distance b...

Mutual information is one of the mostly used measures for evaluating image similarity. In this paper, we investigate the application of three different Tsallis-based generalizations of mutual information to analyze the similarity between scanned documents. These three generalizations derive from the Kullback–Leibler distance, the difference between entropy and conditional entropy, and the Jense...

A prediction interval for a binomial random variable is an important tool in many industry applications. The performance of the existing prediction intervals, however, are unsatisfactory when the true binomial proportion is near a boundary. Since the true proportion can be very small in real applications, in this study, we propose improved prediction intervals with better coverage probability t...

In this paper, we address the importance and the problems involved in topic annotation in the speech retrieval domain. Identified the problem, an algorithm developed to perform automatic topic annotation of broadcast news (BN) speech corpora is described. The approach adopted is based in Hidden Markov Models (HMM) and topic language models, to solve topic segmentation and labelling tasks simult...

Chernoff's bound binds a tail probability (ie. Pr(X ≥ a), where a ≥ EX). Assuming that the distribution of X is Q, the logarithm of the bound is known to be equal to the value of relative entropy (or minus Kullback-Leibler distance) for I-projection ^ P of Q on a set H {P : E P X = a}. Here, Chernoff's bound is related to Maximum Likelihood on exponential form and consequently implications for ...

Irreversibility is one of the most intriguing concepts in physics. While microscopic physical laws are perfectly reversible, macroscopic average behavior has a preferred direction of time. According to the second law of thermodynamics, this arrow of time is associated with a positive mean entropy production. Using a nuclear magnetic resonance setup, we measure the nonequilibrium entropy produce...