Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2390848.2390862 | MIRUM |
Keywords | Field | DocType |
certain sound,dynamic time,temporal salience,audio similarity,human subject study,similarity judgment,time segment,low timbral change,audio similarity measure,high timbral change,novelty measure,query by example | Loudness,Dynamic time warping,Computer science,Speech recognition,Query by Example,Novelty,Salience (language),Salient | Conference |
Citations | PageRank | References |
2 | 0.37 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mark Cartwright | 1 | 25 | 6.78 |
| Bryan Pardo | 2 | 830 | 63.92 |