Content-Based Classification, Search, and Retrieval of Audio
IEEE MultiMedia
A Large-Scale Evaluation of Acoustic and Subjective Music-Similarity Measures
Computer Music Journal
Efficient Index-Based Audio Matching
IEEE Transactions on Audio, Speech, and Language Processing
A unified approach to content-based and fault-tolerant music recognition
IEEE Transactions on Multimedia
MPEG-7 sound-recognition tools
IEEE Transactions on Circuits and Systems for Video Technology
Audio classification based on MPEG-7 spectral basis representations
IEEE Transactions on Circuits and Systems for Video Technology
Content-based audio classification and retrieval by support vector machines
IEEE Transactions on Neural Networks
Proceedings of the international conference on Multimedia
Acoustic detection of elephant presence in noisy environments
Proceedings of the 2nd ACM international workshop on Multimedia analysis for ecological data
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In the past, similarity search for audio data has largely been focused on music. Recent digitization efforts in some of the larger animal sound archives bring other types of audio recordings into the focus of interest. Although recordings in animal sound archives are usually very well annotated by metadata, it is almost impossible to manually annotate all sounds made by animals in each recording. Complementary to classical text-based querying of databases that exploit available annotations, algorithms capable of automatically finding sections of recordings similar to a given query fragment provide a promising approach for content-based navigation. In our work, we present algorithms for feature extraction, as well as indexing and retrieval of animal sound recordings. Making use of a concept from image processing, the structure tensor, our feature extraction algorithm is adapted to the typical curve-like spectral features that are characteristic for many types of animal sounds. We propose a method for similarity search in animal sound databases which is obtained by adding a novel ranking scheme to an existing inverted file based approach for multimedia retrieval. Evaluation of our methods is based on recordings from the Animal Sound Archive, Berlin.