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This paper reviews the state-of-the-art in automatic genre classification of music collections through three main paradigms: expert systems, unsupervised classification, and supervised classification. The paper discusses the importance of music genres with ...
The recognition of speech in meetings poses a number of challenges to current Automatic Speech Recognition (ASR) techniques. Meetings typically take place in rooms with non-ideal acoustic conditions and significant background noise, and may contain large s ...
Audio segmentation, in general, is the task of segmenting a continuous audio stream in terms of acoustically homogenous regions, where the rule of homogeneity depends on the task. This thesis aims at developing and investigating efficient, robust and unsup ...
In this paper, we present initial investigations towards boosting posterior probability based speech recognition systems by estimating more informative posteriors taking into account acoustic context (e.g., the whole utterance), as well as possible prior i ...
In this paper we propose the use of infinite models for the clustering of speakers. Speaker segmentation is obtained trough a Dirichlet Process Mixture (DPM) model which can be interpreted as a flexible model with an infinite a priori number of components. ...
In this paper, we present initial investigations towards boosting posterior probability based speech recognition systems by estimating more informative posteriors taking into account acoustic context (e.g., the whole utterance), as well as possible prior i ...
In this paper we investigate combination of neural net based classifiers using Dempster-Shafer Theory of Evidence. Under some assumptions, combination rule resembles a product of errors rule observed in human speech perception. Different combination are te ...
In this paper we propose the use of infinite models for the clustering of speakers. Speaker segmentation is obtained trough a Dirichlet Process Mixture (DPM) model which can be interpreted as a flexible model with an infinite a priori number of components. ...
The recognition of events in multimedia data is a challenging area of research. The growth in the amount of multimedia data being produced and stored increases the need for systems capable of automatically analysing this data. This analysis can aid in effi ...
In this article, we compare aural and automatic speaker recognition in the context of forensic analyses, using a Bayesian framework for the interpretation of evidence. We use perceptual tests performed by non-experts and compare their performance with that ...
