Application of multiple sound representations in multipitch estimation using shift-invariant probabilistic latent component analysis

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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 SIPLCA 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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9587, pp. 592–601). Springer Verlag. https://doi.org/10.1007/978-3-662-49192-8_48

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