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.

Single Channel Target Speaker Extraction and Recognition with Speaker Beam

Abstract: This paper addresses the problem of single channel speech recognition of a target speaker in a mixture of speech signals. We propose to exploit auxiliary speaker information provided by an adaptation utterance from the target speaker to extract and recognize only that speaker. Using such auxiliary information, we can build a speaker extraction neural network (NN) that is independent of the number of sources in the mixture, and that can track speakers across different utterances, which are two challenging issues occurring with conventional approaches for speech recognition of mixtures. We call such an informed speaker extraction scheme “SpeakerBeam”. SpeakerBeam exploits a recently developed context adaptive deep NN (CADNN) that allows tracking speech from a target speaker using a speaker adaptation layer, whose parameters are adjusted depending on auxiliary features representing the target speaker characteristics. SpeakerBeam was previously investigated for speaker extraction using a microphone array. In this paper, we demonstrate that it is also efficient for single channel speaker extraction. The speaker adaptation layer can be employed either to build a speaker adaptive acoustic model that recognizes only the target speaker or a mask-based speaker extraction network that extracts the target speech from the speech mixture signal prior to recognition. We also show that the latter speaker extraction network can be optimized jointly with an acoustic model to further improve ASR performance.

High-affinity adsorption leads to molecularly ordered interfaces on TiO2 in air and solution

Abstract: Researchers around the world have observed the formation of molecularly ordered structures of unknown origin on the surface of titanium dioxide (TiO2) photocatalysts exposed to air and solution. Using a combination of atomic-scale microscopy and spectroscopy, we show that TiO2 selectively adsorbs atmospheric carboxylic acids that are typically present in parts-per-billion concentrations while effectively repelling other adsorbates, such as alcohols, that are present in much higher concentrations. The high affinity of the surface for carboxylic acids is attributed to their bidentate binding. These self-assembled monolayers have the unusual property of being both hydrophobic and highly water-soluble, which may contribute to the self-cleaning properties of TiO2. This finding is relevant to TiO2 photocatalysis, because the self-assembled carboxylate monolayers block the undercoordinated surface cation sites typically implicated in photocatalysis.

RC models of a constant phase element

Abstract: SUMMARY The paper describes models of a constant-phase element consisting of passive R and C components. The models offer any input impedance argument (phase) between −90° and 0° over a selectable frequency band covering several decades. The design procedure makes it possible to choose values of average phase, phase ripple, frequency bandwidth, and total number of R and C elements. The model can cover three frequency decades with as few as five resistors and five capacitors. The models can be used for practical realization of fractional analog differentiators and integrators, fractional oscillators, chaotic networks or for analog simulation of fractional control systems. Copyright © 2011 John Wiley & Sons, Ltd.