Automatic audio content analysis
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Audio Feature Extraction and Analysis for Scene Segmentation and Classification
Journal of VLSI Signal Processing Systems - special issue on multimedia signal processing
Construction and Evaluation of a Robust Multifeature Speech/Music Discriminator
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 2 - Volume 2
Robust singing detection in speech/music discriminator design
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02
Audio classification in speech and music: a comparison between a statistical and a neural approach
EURASIP Journal on Applied Signal Processing
Statistical modeling and synthesis of intrinsic structures in impact sounds
Statistical modeling and synthesis of intrinsic structures in impact sounds
Audio-based context recognition
IEEE Transactions on Audio, Speech, and Language Processing
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Several sound classifiers have been developed throughout the years. The accuracy provided by these classifiers is influenced by the features they use and the classification method implemented. While there are many approaches in sound feature extraction and in sound classification, most have been used to classify sounds with very different characteristics. Here, we propose a similar sound classifier that is able to distinguish sounds with very similar properties, namely sounds produced by objects with similar geometry and that only differ in material. The classifier applies independent component analysis to learn temporal and spectral features of the sounds, which are then used by a 1-nearest neighbor algorithm. We concluded that the features extracted in this way are powerful enough for classifying similar sounds. Finally, a user study shows that the classifier achieves better performance than humans in the classification of the sounds used here.