Automatic Speaker Recognition System in Adverse Conditions — Implication of Noise and Reverberation on System Performance

Speaker recognition has been developed and evolved over the past few decades into a supposedly mature technique. Existing methods typically utilize robust features extracted from clean speech. In real-world applications, especially security and forensics related ones, reliability of recognition becomes crucial, meanwhile limited speech samples and adverse acoustic conditions, most notably noise and reverberation, impose further complications. This paper is presented from a study into the behavior of typical speaker recognition systems in adverse retrieval phases. Following a brief review, a speaker recognition system was implemented using the MSR Identity Toolbox by Microsoft. Validation tests were carried out with clean speech and the speech contaminated by noise and/or reverberation of varying degrees. The image source method was adopted to take into account real acoustic conditions in the spaces. Statistical relationships between recognition accuracy and signal to noise ratios or reverberation times have therefore been established. Results show noise and reverberation can, to different extents, degrade the performance of recognition. Both reverberation time and direct to reverberation ratio can affect recognition accuracy. The findings may be used to estimate the accuracy of speaker recognition and further determine the likelihood a particular speaker

SPARC 2018 Internationalisation and collaboration : Salford postgraduate annual research conference book of abstracts

Welcome to the Book of Abstracts for the 2018 SPARC conference. This year we not only celebrate the work of our PGRs but also the launch of our Doctoral School, which makes this year’s conference extra special. Once again we have received a tremendous contribution from our postgraduate research community; with over 100 presenters, the conference truly showcases a vibrant PGR community at Salford. These abstracts provide a taster of the research strengths of their works, and provide delegates with a reference point for networking and initiating critical debate. With such wide-ranging topics being showcased, we encourage you to take up this great opportunity to engage with researchers working in different subject areas from your own. To meet global challenges, high impact research inevitably requires interdisciplinary collaboration. This is recognised by all major research funders. Therefore engaging with the work of others and forging collaborations across subject areas is an essential skill for the next generation of researchers

Friction reducing performance of carbon nanotubes covered pistons in internal combustion engines – engine test results

This article discusses the posibility of reducing friction losses in internal combustion engines by using carbon nanotubes, pointing out the large potential of this application. Experimental pistons were made of standard aluminum alloy and coated with a layer of nanotube deposits by spraying them with an aqueous solution containing the binder. The proposed technology of applying layers of nanotubes can be adopted in industrial-scale production. Engine tests were carried out showing a significant reduction of the engine motoring torque, up to 16% for the experimental pistons, thus confirming the favorable tribological properties of nanotubes observed in tribological research and reported by many authors. Supplementary tests were carried out: SEM, EDS, coordinate measuring technique, and x-ray tomography. An alternative technology for hierarchical nanotube multilayer coatings electro-deposition was proposed