Combining Features Reduces Hubness in Audio Similarity.
Sprache des Titels:
Proceedings of the 11th International Society for Music Information Retrieval Conference (ISMIR 2010)
In audio based music similarity, a well known effect is
the existence of hubs, i.e. songs which appear similar to
many other songs without showing any meaningful perceptual
similarity. We verify that this effect also exists in
very large databases (> 250000 songs) and that it even
gets worse with growing size of databases. By combining
different aspects of audio similarity we are able to reduce
the hub problem while at the same time maintaining a high
overall quality of audio similarity.