@inbook{60a6d4ebfa51458694da0c8f0b90d2fc,
title = "Automatic Selection of Pareto-Optimal Topologies of Hidden Markov Models Using Multicriteria Evolutionary Algorithms",
abstract = "In this paper a novel approach of automatic selection of Hidden Markov Models (HMM) structures under Pareto-optimality criteria is presented. Proof of concept is delivered in automatic speech recognition (ASR) discipline where two research scenarios including recognition of speech disorders as well as classification of bird species using their voice are performed. The conducted research unveiled that the Pareto Optimal Hidden Markov Models (POHMM) topologies outperformed both manual structures selection based on theoretical prejudices as well as the automatic approaches that used a single objective only.",
author = "Pawel Swietojanski and Robert Wielgat and Tomasz Zielinski",
year = "2011",
doi = "10.1007/978-3-642-20525-5_23",
language = "English",
isbn = "978-3-642-20525-5",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "224--233",
editor = "{Di Chio}, Cecilia and Stefano Cagnoni and Carlos Cotta and Marc Ebner and Anik{\'o} Ek{\'a}rt and Esparcia-Alc{\'a}zar, {Anna I.} and Merelo, {Juan J.} and Ferrante Neri and Mike Preuss and Hendrik Richter and Julian Togelius and Yannakakis, {Georgios N.}",
booktitle = "Applications of Evolutionary Computation",
address = "United Kingdom",
}