An overview of audio information retrieval
Multimedia Systems - Special issue on audio and multimedia
Robust clustering methods: a unified view
IEEE Transactions on Fuzzy Systems
An integrated approach to fuzzy learning vector quantization and fuzzy c-means clustering
IEEE Transactions on Fuzzy Systems
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Cross-modal correlation learning for clustering on image-audio dataset
Proceedings of the 15th international conference on Multimedia
Smart audio access to multimedia information
AIC'08 Proceedings of the 8th conference on Applied informatics and communications
A Unified Indexing Structure for Efficient Cross-Media Retrieval
DASFAA '09 Proceedings of the 14th International Conference on Database Systems for Advanced Applications
Multi-modal Correlation Modeling and Ranking for Retrieval
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Audio interaction with multimedia information
CIMMACS'09 Proceedings of the 8th WSEAS International Conference on Computational intelligence, man-machine systems and cybernetics
Multi-method audio-based retrieval of multimedia information
WSEAS Transactions on Information Science and Applications
Bridging the gap between visual and auditory feature spaces for cross-media retrieval
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Measuring multi-modality similarities via subspace learning for cross-media retrieval
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
Information Sciences: an International Journal
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Prior work in audio retrieval needs to generate audio templates by supervised learning and find similar audio clip based on pre-trained templates. This paper presents a new and efficient audio retrieval algorithm by unsupervised fuzzy clustering: first, audio features are extracted from compressed domain; second, these features are processed by temporal-spatial constrained fuzzy clustering, and the relevant audio clips can be represented by the clustering centroids; third, we use triangle tree to speedup the similarity measure. Relevance feedback is also implemented during retrieval. Therefore, the result can be adjusted according to users' taste and is consistent with human perception.