Abstract
Audio signal classification has been approached by many researchers, and the purpose of the classification process is needed to build two different libraries: speech library and music library, from a stream of sounds. In this paper, an approach for audio signal classification is proposed using the Wold-Cramer decomposition. Some simulation using the proposed approach is presented.
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References
Fu, Z., Lu, G., Ting, K.M., Zhang, D.: A survey of audio-based music classification and annotation. IEEE Trans. Multimedia 13(2), 303–319 (2011)
Herrera-Boyer P., Amatriain, X., Batlle, E., Serra, X.: Towards instrument segmentation for music content description: a critical review of instrument classification techniques. In: Proceedings of ISMIR, 2000
Srivivas, M., Roy, D., Mohan, C.K.: Learning sparse dictionaries for music and speech classification, ICDSP2014, pp. 673–675 (2014)
Biagetti, G., Crippa, P., Turchetti, C., Morici, A.: Efficient synthesis of piano tones with damped bessel functions. In: IEEE Proceedings of 15th International Conference on Digital Signal Processing (DSP 2007), Cardiff, Galles, UK, pp. 539–542, 1–4 July 2007
Lu, M., Dou, W.: Butterfly-like D-tree fusion strategy for real-time speech and music classification, ICMEW2014, pp. 1–4 (2014)
Al-Shoshan, A.I.: Speech and music classification and separation: a review. J. King Saud Univ. Eng. Sci. 19(1), 95–133 (2006)
El-Maleh, K., Klein, M., Petrucci, G., Kabal, P.: Speech/music discriminator for multimedia application. In: Proceedings of IEEE ICASSP pp. 2445–2448 (2000)
Ramalingam, T., Dhanalakshmi, P.: Speech/music classification using wavelet based feature extraction techniques. J. Comput. Sci. 10, 34–44 (2014)
Ghoraani, B., Krishnan, S.: Time-frequency matrix feature extraction and classification of environmental audio signals. IEEE Trans. Audio Speech Lang. Process 19(7), 2197–2209 (2011)
Jain, A.K., Duin, R.P.W., Jianchang, Mao: Statistical pattern recognition: a review. IEEE Trans. Pattern Anal. Mach. Intell. 22(1), 4–37 (2000)
Gianfelici, F., et al.: A non-probabilistic recognizer of stochastic signals based on KLT. Sig. Process. 89(4), 422–437 (2009)
Biagetti, G., Crippa, P., Turchetti, C.: Modeling of speech signals based on bessel-like orthogonal transform. In: Proceedings of Interspeech 2006—ICSLP Ninth International Conference on Spoken Language Processing, Pittsburgh, PA, U.S.A., 2478–2481, 17–21 Sept 2006
Saunders, J.: Real-time discrimination of broadcast speech/music. IEEE ICASSP’96, pp. 993–996 (1996)
Al-Shoshan, A.I., Al-Atiyah, A., Al-Mashouq, K.: A three-level speech, music, and mixture classifier. J. King Saud Univ. Eng. Sci. 16(2), 319–332 (2004)
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Al-Shoshan, A.I. (2016). A Classification of an Audio Signal Using the Wold-Cramer Decomposition. In: Sulaiman, H., Othman, M., Othman, M., Rahim, Y., Pee, N. (eds) Advanced Computer and Communication Engineering Technology. Lecture Notes in Electrical Engineering, vol 362. Springer, Cham. https://doi.org/10.1007/978-3-319-24584-3_40
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DOI: https://doi.org/10.1007/978-3-319-24584-3_40
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