In this paper global similarity features that improve speaker clustering based on standard bottom-up clustering are proposed. The novelty of this approach lies in the fact that it exploits the hypothesis that audio segments belonging to the same speaker cluster should demonstrate similar global behavior, exhibit the same similarity and dissimilarity with all the other segments. Every segment is...

Extreme learning machine (ELM) has shown its good performance in regression applications with a very fast speed. But there is still a difficulty to compromise between better generalization performance and smaller complexity of the ELM (number of hidden nodes). This paper proposes a method called Delta TestELM (DT-ELM), which operates in an incremental way to create less complex ELM structures a...

Behavioural sleep problems, that is, sleep problems that do not have a physiological aetiology, but rather a behavioural or psychological aetiology, are reported in between 20% 40% of children and adolescents. These sleep disorders are categorised as Behavioural Insomnia of Childhood (BIC) in the International Classification of Sleep Disorders. BIC can result in short sleep duration and poor qu...

A widely adopted algorithm for the audio segmentation is based on the Bayesian Information Criterion (BIC), applyed within a sliding variable-size analysis window. In this work, three different implementations of that algorithm are analyzed in detail: (i) one that keeps updated a pair of sums, that of input vectors and that of square input vectors, in order to save computations in estimating co...

The aim of a crisp cluster validity index is to quantify the quality of a given data partition. It allows to select the best partition out of a set of potential ones, and to determine the number of clusters. Recently, negentropy-based cluster validation has been introduced. This new approach seems to perform better than other state of the art techniques, and its computation is quite simple. How...

We present a novel scheme for indexing “hot spots” in conversations, such as poster sessions, based on the reaction of the audience. Specifically, we focus on laughters and non-lexical reactive tokens, which are presumably related with funny spots and interesting spots, respectively. A robust detection method of these acoustic events is realized by combining BIC-based segmentation and GMM-based...

Bayesian Information Criterion (BIC) is a promising method for detecting the number of clusters. It is often used in model-based clustering in which a decisive first local maximum is detected as the number of clusters. In this paper, we re-formulate the BIC in partitioning based clustering algorithm, and propose a new knee point finding method based on it. Experimental results show that the pro...

This paper proposes an approach for unsupervised speaker segmentation and gender discrimination of broadcast news. In this paradigm, a speaker segmentation mechanism using MDL-based Gaussian model is firstly adopted to determine the speaker changes using mean and covariance of the Gaussian model. These speaker segments partitioned by speaker changes are smoothed and discriminated into male or f...

In this paper we consider the problem of detecting speaker changes in audio signals recorded by distant microphones. It is shown that the possibility to exploit the spatial separation of speakers more than makes up the degradation in detection accuracy due to the increased source-to-sensor distance compared to close-talking microphones. Speaker direction information is derived from the filter c...