Abstract
The objective of the presented study is to show that it is possible to effectively separate harmonic sounds from musical sound mixtures for the purpose of automatic sounds recognition, without any prior knowledge of the mixed instruments. It has also been shown that a properly trained ANN enables to reliably validate separation results of mixed musical instrument sounds, and the validation corresponds with subjective perception of the separated sounds quality. A comparison between the results obtained with the use of the ANN-based recognition, subjective evaluation of the separation performance and the energy-based evaluation is provided.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Dziubiński, M., Dalka, P., Kostek, B.: Estimation of Musical Sound Separation Algorithm Effectiveness Employing Neural Networks. J. Intel. Inform. Systems 24(2), 133–157 (2005)
Dziubiński, M., Kostek, B.: Octave Error Immune and Instantaneous Pitch Detection Algorithm. J. New Music Research 34, 273–292 (2005)
Dziubiński, M.: Musical Instrument Sound Separation Methods Supported by Artificial Neural Network Decision System, Ph.D. thesis, MSD, GUT (2006)
Gillet, O., Richard, G.: Transcription and separation of drum signals from polyphonic music. IEEE Transactions on Audio, Speech and Language Processing 16, 529–540 (2008)
http://ismir2009.ismir.net (Intern. Conference on Music Information Retrieval website)
Klapuri, A.: Multipitch analysis of polyphonic music and speech signals using an auditory model. IEEE Trans. Audio, Speech and Language Processing 16(2), 255–266 (2008)
Klapuri, A.: Multipitch estimation and sound separation by the spectral smoothness principle. In: Proc. IEEE ICASSP 2001, Salt Lake City, USA, pp. 3381–3384 (2001)
Kostek, B.: Perception-Based Data Processing in Acoustics. Springer, Berlin (2005)
Kostek, B., Czyzewski, A.: Representing Musical Instrument Sounds for their Automatic Classification. J. Audio Eng. Soc. 49, 768–785 (2001)
Kostek, B.: Applying computational intelligence to musical acoustics. Archives of Acoustics 32(3), 617–629 (2007)
Quatieri, T.F., McAulay, R.J.: Magnitude-only reconstruction using a sinusoidal speech model. In: Proc. IEEE ICASSP 1984, vol. 2, pp. 27.6.1–27.6.4 (1984)
Tzanetakis, G.: Signal Processing Methods for Music Transcription Computer Music J., 32(4), 86-88 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Dziubiński, M., Kostek, B. (2010). Evaluation of the Separation Algorithm Performance Employing ANNs. In: Nguyen, N.T., Zgrzywa, A., Czyżewski, A. (eds) Advances in Multimedia and Network Information System Technologies. Advances in Intelligent and Soft Computing, vol 80. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14989-4_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-14989-4_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14988-7
Online ISBN: 978-3-642-14989-4
eBook Packages: EngineeringEngineering (R0)