Dafx: Digital Audio Effects
Neural Mechanisms of Involuntary Attention to Acoustic Novelty and Change
Journal of Cognitive Neuroscience
Disorder inequality: a combinatorial approach to nearest neighbor search
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Sound retrieval and ranking using sparse auditory representations
Neural Computation
Content search through comparisons
ICALP'11 Proceedings of the 38th international conference on Automata, languages and programming - Volume Part II
Divergence measures based on the Shannon entropy
IEEE Transactions on Information Theory
Proceedings of the 20th ACM international conference on Multimedia
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Most algorithms for estimating audio similarity either completely disregard time or they treat each moment in time equally. However, many studies over the years have noted several factors that affect how much attention we give to certain sounds or parts of sounds (e.g. loudness, the attack, novelty). These findings suggest that some time segments of audio may be more salient than others when making similarity judgments. We believe that if we could estimate this information, we could improve audio similarity measures. This paper presents the results of a human subject study designed to test the hypothesis that sounds segments with high timbral change are more salient than segments with low timbral change. We then investigate whether we can use this information to improve two audio similarity measures: a "bag-of-frames" approach and a dynamic time warping approach.