Abstract
With the explosive growth of digital music content-based music information retrieval especially query by humming/singing have been attracting more and more attention and are becoming popular research topics over the past decade. Although query by humming/singing can provide natural and intuitive way to search music, retrieval system still confronts many issues such as key modulation, tempo change, note insertion, deletion or substitution which are caused by users and query transcription respectively. In this paper, we propose a novel approach based on fault tolerance and recursive segmentation to solve above problems. Music melodies in database are represented with specified manner and indexed using inverted index method. Query melody is segmented into phrases recursively with musical dictionary firstly. Then improved edit distance, pitch deviation and overall bias are employed to measure the similarity between phrases and indexed entries. Experimental results reveal that proposed approach can achieve high recall for music retrieval.
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
Yahoo, http://music.cn.yahoo.com/
Heo, S.P., Suzuki, M., Ito, A., Makino, S.: An Effective Music Information Retrieval Method Using Three-Dimensional Continuous DP. IEEE Trans. on Multimedia 8(3), 633–639 (2006)
Suyoto, I.S.H., Uitdenbogerd, A.L., Scholer, F.: Searching Musical Audio Using Symbolic Queries. IEEE Trans. on Audio, Speech and Language 16(2), 372–381 (2008)
Pauws, S.: CubyHum: A Fully Operational Query by Humming System. In: Proceedings of International Society for Music Information Retrieval Conference, ISMIR (2002)
Unal, E., Narayanan, S., Chew, E., Georgiou, P.G., Dahlin, N.: A Dictionary Based Approach for Robust and Syllable-Independent Audio Input Transcript for Query by Humming Systems. In: Proceedings of International Conference of ACM Multimedia 2006, pp. 37–43 (2006)
Ryynanen, M., Klapuri, A.: Query by Humming of MIDI and Audio Using Locality Sensitive Hashing. In: Proceedings of International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 2249–2252 (2008)
Mulder, T.D., Martens, J.P., Pauws, S., Vignoli, F., Lesaffre, M.: Factors Affecting Music Retrieval in Query-by-Melody. IEEE Trans. on Multimedia 8(4), 728–739 (2006)
Unal, E., Chew, E., Georgiou, P.G., Narayanan, S.S.: Challenging Uncertainty in Query by Humming Systems: A Fingerprinting Approach. IEEE Trans. on Audio, Speech and Language 16(2), 359–371 (2008)
Hsu, J.L., Liu, C.C., Chen, A.L.P.: Discovering Nontrivial Repeating Patterns in Music Data. IEEE Trans. on Multimedia 3(3), 311–325 (2001)
Liu, N.-H., Wu, Y.-H., Chen, A.L.P.: An efficient approach to extracting approximate repeating patterns in music databases. In: Zhou, L.-z., Ooi, B.-C., Meng, X. (eds.) DASFAA 2005. LNCS, vol. 3453, pp. 240–252. Springer, Heidelberg (2005)
Essen Folk Song Database, http://www.esac-data.org/
Rho, S., Han, B.J., Hwang, E., Kim, M.: MUSEMBLE: A Novel Music Retrieval System with Automatic Voice Query Transcription and Reformulation. The Journal of Systems and Software, 1065–1080 (2008)
Cheveigne, A.D., Kawahara, H.: YIN, A Fundamental Frequency Estimatior for Speech and Music. Journal of the Acoustical Society of America 111(4), 1917–1930 (2002)
Kosugi, N., Sakurai, Y., Morimoto, M.: SoundCompass: A Practial Query-by-Humming System. In: Proceedings of ACM SIGMOD 2004 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yang, X., Chen, Q., Wang, X. (2010). A Novel Approach Based on Fault Tolerance and Recursive Segmentation to Query by Humming. In: Kim, Th., Adeli, H. (eds) Advances in Computer Science and Information Technology. AST ACN 2010 2010. Lecture Notes in Computer Science, vol 6059. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13577-4_49
Download citation
DOI: https://doi.org/10.1007/978-3-642-13577-4_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13576-7
Online ISBN: 978-3-642-13577-4
eBook Packages: Computer ScienceComputer Science (R0)