Abstract
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.
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Berenzweig, A.L., Ellis, D.: Locating singing voice segments within music signals. In: Proc. IEEE Workshop on Apps. of Sig. Proc. to Acous. and Audio, pp. 119–122 (2001)
Breebaart, J., McKinney, M.: Features for audio classification. In: Proc. Philips Symposium on Intelligent Algorithms, Eindhoven (2002)
Bugatti, A., Flammini, A., Migliorati, P.: Audio classification in speech and music: a comparison between a statistical and a neural approach. Applied Signal Processing (1), 372–378 (2002)
Cavaco, S.: Statistical modeling and synthesis of intrinsic structures in impact sounds. PhD thesis, Carnegie Mellon University (2007)
Cavaco, S., Lewicki, M.S.: Statistical modeling of intrinsic structures in impact sounds. Journal of the Acoustical Society of America 121(6), 3558–3568 (2007)
Chou, W., Gi, L.: Robust singing detection in speech/music discriminator design. In: Proceedings of the Acoustics, Speech, and Signal Processing on IEEE International Conference, pp. 865–868 (2001)
Chu, S., Narayanan, S., J Kuo, C.-C.: Environmental sound recognition using MP-based features. In: Proc. IEEE ICASSP, pp. 1–4 (2008)
Eronen, A.: Musical instrument recognition using ICA-based transform of features and discriminatively trained HMMs. Signal Processing and Its Applications 2, 133–136 (2003)
Eronen, A.J., Peltonen, V.T., Tuomi, J.T., Klapuri, A.P., Fagerlund, S., Sorsa, T., Lorho, G., Huopaniemi, J.: Audio-based context recognition. Audio, Speech, and Language Processing 14(1), 321–329 (2006)
Hyvärinen, A., Karhunen, J., Oja, E.: Independent component analysis. John Wiley & sons, Ltd., Chichester (2001)
Kraft, F., Schaaf, T., Waibel, A., Malkin, R.: Temporal ICA for classification of acoustic events in a kitchen environment. In: Proc. International Conference on Speech and Language Processing - Interspeech, pp. 2689–2692 (2005)
Liu, Z., Wang, Y., Chen, T.: Audio feature extraction and analysis for scene segmentation and classification. The Journal of VLSI Signal Procesing 20(1-2), 61–79 (1998)
Ma, L., Smith, D.J., Milner, B.P.: Context awareness using environmental noise classification. In: Proc. of Eurospeech, vol. 3, pp. 2237–2240 (2003)
Nóbrega, R., Cavaco, S.: Detecting key features in popular music: case study - singing voice detection. In: Ramirez, R., Conklin, D., Anagnostopoulou, C. (eds.) Proc. of the Workshop on Machine Learning and Music of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (2009)
Ntalampiras, S., Potamitis, I., Fakotakis, N.: Automatic recognition of urban environmental sounds events. New Directions in Intelligent Interactive Multimedia, 147–153 (2008)
Pfeiffer, S., Fischer, S., Effelsberg, W.: Automatic audio content analysis. In: Proc. of ACM International Conference on Multimedia, pp. 21–30 (1997)
Scheirer, E., Slaney, M.: Construction and evaluation of a robust multifeature speech/music discriminator. In: Proc. IEEE ICASSP, vol. 2, pp. 1331–1334 (1997)
Tzanetakis, G., Essl, G., Cook, P.: Audio analysis using the discrete wavelet transform. In: Proc. Conference in Acoustics and Music Theory Applications (2001)
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Cavaco, S., Rodeia, J. (2010). Classification of Similar Impact Sounds. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D., Meunier, J. (eds) Image and Signal Processing. ICISP 2010. Lecture Notes in Computer Science, vol 6134. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13681-8_36
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DOI: https://doi.org/10.1007/978-3-642-13681-8_36
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