Research on individuality features in speech waves and automatic speaker recognition techniques
Speech Communication - Special issue: Speech research in Japan
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Fundamentals of speech recognition
Fundamentals of speech recognition
Non-linear dimensionality reduction techniques for unsupervised feature extraction
Pattern Recognition Letters
Unsupervised feature selection using a neuro-fuzzy approach
Pattern Recognition Letters
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
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This paper is a contribution to probabilistic data mining and pattern recognition. A DTW-based statistical model is proposed to explore the subspace structures of speaker feature space for feature evaluation, dimension reduction and inter-class information discovery in pattern space. We demonstrate its usefulness in isolated digits speaker identification, and the performance of the statistical model is compared with standard DTW recognition rate in the experiment. We argue that the probability model can be taken as data mining tools.