Development of a speaker recognition system using wavelets and artificial neural networks

This paper addresses the problem of speaker recognition from speech signals. The study focuses on the development of a speaker recognition system comprising two modules: a wavelet-based feature extractor, and a neural-network-based classifier. We have conducted a number of experiments to investigate the applicability of Discrete Wavelet Transform (D WT) in extracting discriminative features from the speech signals, and have examined various models from the Adaptive Resonance Theory (ART) family of neural networks in classijjing the extracted features. The results indicate that DWT could be a potential feature extraction tool for speaker recognition. In addition, the ART-based classijiers have yielded very promising recognition accuracy at more than 81%.

Are voluntary wheel running and open-field behavior correlated in mice? Different answers from comparative and artificial selection approaches

Voluntary wheel running and open-field behavior are probably the two most widely used measures of locomotion in laboratory rodents. We tested whether these two behaviors are correlated in mice using two approaches: the phylogenetic comparative method using inbred strains of mice and an ongoing artificial selection experiment on voluntary wheel running. After taking into account the measurement error and phylogenetic relationships among inbred strains, we obtained a significant positive correlation between distance run on wheels and distance moved in the open-field for both sexes. Thigmotaxis was negatively correlated with distance run on wheels in females but not in males. By contrast, mice from four replicate lines bred for high wheel running did not differ in either distance covered or thigmotaxis in the open field as compared with mice from four non-selected control lines. Overall, results obtained in the selection experiment were generally opposite to those observed among inbred strains. Possible reasons for this discrepancy are discussed.

The pace of life under artificial selection : personality, energy expenditure, and longevity are correlated in domestic dogs

The domestic dog has undergone extensive artificial selection resulting in an extreme diversity in body size, personality, life‐history, and metabolic traits among breeds. Here we tested whether proactive personalities (high levels of activity, boldness, and aggression) are related to a fast “pace of life” (high rates of growth, mortality, and energy expenditure). Data from the literature provide preliminary evidence that artificial selection on dogs (through domestication) generated variations in personality traits that are correlated with life histories and metabolism. We found that obedient (or docile, shy) breeds live longer than disobedient (or bold) ones and that aggressive breeds have higher energy needs than unaggressive ones. These correlations could result from either human preference for particular trait combinations or, more likely, correlated responses to artificial selection on personality. Our results suggest the existence of a general pace‐of‐life syndrome arising from the coevolution of personality, metabolic, and life‐history traits.