Brno University of Technology

About: Brno University of Technology is a education organization based out in Brno, Czechia. It is known for research contribution in the topics: Fracture mechanics & Filter (video). The organization has 6339 authors who have published 15226 publications receiving 194088 citations. The organization is also known as: Vysoké učení technické v Brně & BUT.

Discriminatively trained Probabilistic Linear Discriminant Analysis for speaker verification

Abstract: Recently, i-vector extraction and Probabilistic Linear Discriminant Analysis (PLDA) have proven to provide state-of-the-art speaker verification performance. In this paper, the speaker verification score for a pair of i-vectors representing a trial is computed with a functional form derived from the successful PLDA generative model. In our case, however, parameters of this function are estimated based on a discriminative training criterion. We propose to use the objective function to directly address the task in speaker verification: discrimination between same-speaker and different-speaker trials. Compared with a baseline which uses a generatively trained PLDA model, discriminative training provides up to 40% relative improvement on the NIST SRE 2010 evaluation task.

What practitioners consider to be the skills and behaviours of an effective people project manager

Abstract: It is recognized by academics and the community of practice that the management of people plays an important role in project management. Recent people skills research expresses the need to develop a better understanding of what good people management is. This paper proposes what project management practitioners consider to be skills and behaviours of an effective people project manager. A combination of literature review, face to face interviews and focus group meetings was applied to complete the research objective. Six specific skills and associated behaviours were identified as being most important. The results suggest that project managers would benefit from adopting these skills and behaviours to strengthen their managing people skills and behaviours to improve the successful delivery of projects. The findings also suggest that some skill sets and behaviours may be more appropriate for application in certain project environments such as IT or the construction industry.

Subspace Gaussian Mixture Models for speech recognition

Abstract: We describe an acoustic modeling approach in which all phonetic states share a common Gaussian Mixture Model structure, and the means and mixture weights vary in a subspace of the total parameter space. We call this a Subspace Gaussian Mixture Model (SGMM). Globally shared parameters define the subspace. This style of acoustic model allows for a much more compact representation and gives better results than a conventional modeling approach, particularly with smaller amounts of training data.

Multilingual acoustic modeling for speech recognition based on subspace Gaussian Mixture Models

Abstract: Although research has previously been done on multilingual speech recognition, it has been found to be very difficult to improve over separately trained systems. The usual approach has been to use some kind of “universal phone set” that covers multiple languages. We report experiments on a different approach to multilingual speech recognition, in which the phone sets are entirely distinct but the model has parameters not tied to specific states that are shared across languages. We use a model called a “Subspace Gaussian Mixture Model” where states' distributions are Gaussian Mixture Models with a common structure, constrained to lie in a subspace of the total parameter space. The parameters that define this subspace can be shared across languages. We obtain substantial WER improvements with this approach, especially with very small amounts of in-language training data.