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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 4 of 4 1 Expanding Parallel Resources for Medium-Density Languages for Free Georgi Iliev; Angel Genov In: http://www.mt-archive.info/LREC-2012-Iliev.pdf BASE Show details 2 Expanding Parallel Resources for Medium-Density Languages for Free Georgi Iliev; Angel Genov In: http://www.lrec-conf.org/proceedings/lrec2012/pdf/743_Paper.pdf BASE Show details 3 1#. A Methodology and a System for Adaptive Speech Recognition in a Noisy Environment Based on Adaptive Noise Cancellation and Evolving Fuzzy Neural Networks Nikola Kasabov; Georgi Iliev In: http://www.aut.ac.nz/__data/assets/pdf_file/0015/10608/iliev-kas-ch.pdf Abstract: Speech and signal processing technologies need new methods that deal with the problems of noise and adaptation in order for these technologies to become common tools for communication and information processing. This chapter is concerned with a method and a system for adaptive speech recognition in a noisy environment (ASN). A system based on the described method can store words and phrases spo-ken by the user and subsequently recognise them when they are pronounced as con-nected words in a noisy environment. The method guarantees system robustness in respect to noise, regardless of its origin and level. New words, pronunciations, and languages can be introduced to the system in an incremental, adaptive mode. The method and system are based on novel techniques recently created by the authors, namely: adaptive noise suppression, and evolving connectionist systems. Potential applications are numerous, e.g. voice dialling in a noisy environment, voice com-mand control, improved wireless communications, data entry into databases, helping disabled people, multimedia systems, improved human computer interaction. The method and system are illustrated on the recognition of English spoken digits in dif-ferent noisy environments. URL: http://www.aut.ac.nz/__data/assets/pdf_file/0015/10608/iliev-kas-ch.pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.606.7546 BASE Hide details 4 Hybrid System for Robust Recognition of Noisy Speech Based on Evolving Fuzzy Neural Networks and Adaptive Filtering Nikola Kasabov; Georgi Iliev In: http://www.aut.ac.nz/resources/research/research_institutes/kedri/downloads/pdf/iliev-kas-ijcnn2000.pdf BASE Show details

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