Introduction to artificial neural systems
Introduction to artificial neural systems
Data mining solutions: methods and tools for solving real-world problems
Data mining solutions: methods and tools for solving real-world problems
Data mining methods for knowledge discovery
Data mining methods for knowledge discovery
A formal framework for linguistic annotation
Speech Communication - Special issue on speech annotation and corpus tools
Heterogeneous relation graphs as a formalism for representating linguistic information
Speech Communication - Special issue on speech annotation and corpus tools
Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Brain-like Computing and Intelligent Information Systems
Brain-like Computing and Intelligent Information Systems
IEEE Transactions on Fuzzy Systems
A decade of Kasabov's evolving connectionist systems: a review
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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This paper presents some preliminary results of an original study to model the emergence of bilingual acoustic clusters of both New Zealand English and New Zealand Maori speech. This is performed using true on-line learning in a connectionist architecture. The study represents a joint collaborative analysis, which applies the bilingual data as training examples to a connectionist-based evolving clustering method algorithm. The algorithm returns a structure containing acoustic clusters plotted using visualization techniques that could be used as the foundations for future speech classification systems. The following experiments are based on the notion that approximately 75% of the phonological units in New Zealand English and New Zealand Maori occupy similar acoustic space, they sound the same, and therefore they can be used to classify new unknown speech units or words.