A variety of techniques from statistics, signal processing, pattern recognition, machine learning, and neural networks have been proposed to understand data by discovering useful categories. However, research in data mining has not paid attention to the cognitive factors that make learned categories intelligible to human users. We ohnwr +hn+ _,.a Cnnte... the+ ;nfl.,nmnao thn ;ntczll;~.;h:l;+.r...

BACKGROUND The well-established left hemisphere specialisation for language processing has long been claimed to be based on a low-level auditory specialization for specific acoustic features in speech, particularly regarding 'rapid temporal processing'. METHODOLOGY A novel analysis/synthesis technique was used to construct a variety of sounds based on simple sentences which could be manipulat...

Traditionally, explainable artificial intelligence seeks to provide explanation and interpretability of high-performing black-box models such as deep neural networks. Interpretation remains difficult, because their high complexity. An alternative method is instead force a deep-neural network use human-intelligible features the basis for its decisions. We tested this approach using natural categ...

An anterior pathway, concerned with extracting meaning from sound, has been identified in nonhuman primates. An analogous pathway has been suggested in humans, but controversy exists concerning the degree of lateralization and the precise location where responses to intelligible speech emerge. We have demonstrated that the left anterior superior temporal sulcus (STS) responds preferentially to ...

In order to compare the effects of different acoustic transmission conditions on Mandarin consonants perception, two subjective speech intelligibility tests were separately carried out in reverberant and noisy condition. The results showed that the affricates and fricatives were the most intelligible in reverberation. Friction might be the most important cue for consonant perception in reverber...