Title :
Mixtures of probability experts for audio retrieval and indexing
Author_Institution :
IBM Almaden Res. Center, San Jose, CA, USA
Abstract :
This paper describes a system for connecting nonspeech sounds and words using linked multidimensional vector spaces. An approach based on a mixture of experts learns the mapping between one space and the other. This paper describes the conversion of audio and semantic data into their respective vector spaces. Two different mixture-of-probability-expert models are trained to learn the association between acoustic queries and the corresponding semantic explanation, and vice versa. Test results are presented based on commercial sound effects CD.
Keywords :
audio databases; content-based retrieval; data mining; database indexing; expert systems; learning (artificial intelligence); probability; acoustic queries; audio indexing; audio retrieval; commercial sound effects CD; linked multidimensional vector spaces; mapping learning; mixture-of-probability-expert models; nonspeech sounds; semantic data; semantic explanation; training; words; Acoustic testing; Audio recording; Dogs; Extraterrestrial measurements; Horses; Indexing; Joining processes; Space shuttles; Surface fitting; Web pages;
Conference_Titel :
Multimedia and Expo, 2002. ICME '02. Proceedings. 2002 IEEE International Conference on
Print_ISBN :
0-7803-7304-9
DOI :
10.1109/ICME.2002.1035789