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.

Simplification and optimization of i-vector extraction

Abstract: This paper introduces some simplifications to the i-vector speaker recognition systems. I-vector extraction as well as training of the i-vector extractor can be an expensive task both in terms of memory and speed. Under certain assumptions, the formulas for i-vector extraction—also used in i-vector extractor training—can be simplified and lead to a faster and memory more efficient code. The first assumption is that the GMM component alignment is constant across utterances and is given by the UBM GMM weights. The second assumption is that the i-vector extractor matrix can be linearly transformed so that its per-Gaussian components are orthogonal. We use PCA and HLDA to estimate this transform.

Transcribing Meetings With the AMIDA Systems

Abstract: In this paper, we give an overview of the AMIDA systems for transcription of conference and lecture room meetings. The systems were developed for participation in the Rich Transcription evaluations conducted by the National Institute for Standards and Technology in the years 2007 and 2009 and can process close talking and far field microphone recordings. The paper first discusses fundamental properties of meeting data with special focus on the AMI/AMIDA corpora. This is followed by a description and analysis of improved processing and modeling, with focus on techniques specifically addressing meeting transcription issues such as multi-room recordings or domain variability. In 2007 and 2009, two different strategies of systems building were followed. While in 2007 we used our traditional style system design based on cross adaptation, the 2009 systems were constructed semi-automatically, supported by improved decoders and a new method for system representation. Overall these changes gave a 6%-13% relative reduction in word error rate compared to our 2007 results while at the same time requiring less training material and reducing the real-time factor by five times. The meeting transcription systems are available at www.webasr.org.

PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions.

Abstract: An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools’ predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To enable comprehensive evaluation of variants, the predictions are complemented with annotations from eight databases. The web server is freely available to the community at http://loschmidt.chemi.muni.cz/predictsnp2.

Bifidobacterium longum CCM 7952 Promotes Epithelial Barrier Function and Prevents Acute DSS-Induced Colitis in Strictly Strain-Specific Manner

Abstract: Background Reduced microbial diversity has been associated with inflammatory bowel disease (IBD) and probiotic bacteria have been proposed for its prevention and/or treatment. Nevertheless, comparative studies of strains of the same subspecies for specific health benefits are scarce. Here we compared two Bifidobacterium longum ssp. longum strains for their capacity to prevent experimental colitis. Methods Immunomodulatory properties of nine probiotic bifidobacteria were assessed by stimulation of murine splenocytes. The immune responses to B. longum ssp. longum CCM 7952 (Bl 7952) and CCDM 372 (Bl 372) were further characterized by stimulation of bone marrow-derived dendritic cell, HEK293/TLR2 or HEK293/NOD2 cells. A mouse model of dextran sulphate sodium (DSS)-induced colitis was used to compare their beneficial effects in vivo. Results The nine bifidobacteria exhibited strain-specific abilities to induce cytokine production. Bl 372 induced higher levels of both pro- and anti-inflammatory cytokines in spleen and dendritic cell cultures compared to Bl 7952. Both strains engaged TLR2 and contain ligands for NOD2. In a mouse model of DSS-induced colitis, Bl 7952, but not Bl 372, reduced clinical symptoms and preserved expression of tight junction proteins. Importantly, Bl 7952 improved intestinal barrier function as demonstrated by reduced FITC-dextran levels in serum. Conclusions We have shown that Bl 7952, but not Bl 372, protected mice from the development of experimental colitis. Our data suggest that although some immunomodulatory properties might be widespread among the genus Bifidobacterium, others may be rare and characteristic only for a specific strain. Therefore, careful selection might be crucial in providing beneficial outcome in clinical trials with probiotics in IBD.