Abstract
This paper describes the way of Music Retrieval Method based on audio feature analysis techniques which is proposed with three major new algorithms to improve performance of conventional way and implements the whole system including client and server side prototype. The first one of the major algorithms is to extract the high level melody feature from polyphonic music using harmonic structure attribute. The second one is to extract the feature and suppress the noise from user humming signal. The last one is fusing the way of methods with Dynamic Time Warp (DTW), Linear Scaling (LS) and Quantized Binary Code (QBCode). This has focused on targeting of commercial services such as music portal services, fixed stand-alone devices, mobile devices, and so on.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Orio, N.: Music Information Retrieval: A turorial and review. Found. Trends. Inf. Retr. 1, 1–90 (2006)
ITU-T, Recommendation G.729: Coding of speech at 8 kbit/s using CS-ACELP (March 1996)
Kamath, S., Loizou, P.: A multi-band spectral subtraction method for enhancing speech corrupted by colored noise. In: IEEE ICASSP (2002)
Poliner, G., Ellis, D.P., Ehamann, A.F., Gomez, E., Streich, S., Ong, B.: Melody Transcription from Music Audio: Approaches and Evaluation. IEEE Trans. Audio, Speech and Language Process. 15(4), 1066–1074 (2007)
Eggink, J., Broown, G.J.: Extracting melody lines from complex audio. ISMIR (2004)
Klapuri, A.: Multiple Fundamental Frequency Estimation by Summing Harmonic Amplitude. IEEE Trans. Speech and Audio Processing 8(6) (2003)
Goto, M.: A real-time music scene description system: Predominant-F0 estimation for detecting melody and bass lines in real-world audio signals. Speech Communication 43(4), 311–329 (2004)
Jang, J.-S.R., Lee, H.-R.: A General Framework of Progressive Filtering and Its Application to Query by Singing/Humming. IEEE Trans. Speech, Audio and Language 2(16), 250–258 (2008)
de Cheveigne, A., Kawahara, H.: YIN, a fundamental frequency estimator for speech and music. Journal ASA 111 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Song, CJ., Lee, SP., Park, H. (2011). The Contents Based Music Retrieval Method Using Audio Feature Analysis against Polyphonic Music. In: Kim, Th., Adeli, H., Robles, R.J., Balitanas, M. (eds) Information Security and Assurance. ISA 2011. Communications in Computer and Information Science, vol 200. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23141-4_25
Download citation
DOI: https://doi.org/10.1007/978-3-642-23141-4_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23140-7
Online ISBN: 978-3-642-23141-4
eBook Packages: Computer ScienceComputer Science (R0)