Abstract
Probabilistic analysis has become one of the most important directions for development of new methods in Music Information Retrieval (MIR) field. Its ability to correctly find necessary information in the music audio recordings is especially useful in multipitch estimation, a vital task belonging to the MIR field. Since the multipitch estimation is still far from being resolved, it is important to enhance the existing state-of-the-art methods. Usually, a spectrogram, generated from the Constant-Q transform (CQT) is used as a basis for the SI-PLCA method. The new approach involves application of more than one method (cepstrum and CQT) in association of the shift-invariant probabilistic latent component analysis approach and additional processing of all the sound representations, in order to achieve better results.
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Rychlicki-Kicior, K., Stasiak, B., Yatsymirskyy, M. (2016). Application of Multiple Sound Representations in Multipitch Estimation Using Shift-Invariant Probabilistic Latent Component Analysis. In: Freivalds, R., Engels, G., Catania, B. (eds) SOFSEM 2016: Theory and Practice of Computer Science. SOFSEM 2016. Lecture Notes in Computer Science(), vol 9587. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49192-8_48
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DOI: https://doi.org/10.1007/978-3-662-49192-8_48
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