Skip to main content
Log in

Design of database for evaluating 3D audio core algorithms

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

In this paper, we develop 3D audio evaluation database (DB) for verifying performance of new developed 3D audio core algorithms such as sound source localization, artificial reverberation, source separation, and crosstalk cancellation. Our system is designed to evaluate the 3D audio core algorithms automatically. Conventional evaluation DBs have to be executed manually for evaluating audio systems because the audio sources are not indexed in general. To solve this problem, we propose the architecture of 3D audio core algorithm evaluation database using database management system (DBMS). In the experimental section, we show feasibility of our system using real 3D sound sources for sound source separation algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  1. Abhijit Jukjarni H, Colburn S (1998) Role of spectral detail in sound-source localization. Hear Res Cent Depart Biomed Eng Boston Univ 396:747–749

    Google Scholar 

  2. Algazi VR, Duda RO, Thompson DM, Avendano C (2001) The cipic HRTF database. Creat Adv Technol Cent. doi:10.1109/ASPAA.2001.969552

  3. Belouchrni A, Abed-Meraim K, Cardoso JF, Moulines E (1997) A blind source separation technique using second-order statistics. IEEE 45:434–443

    Google Scholar 

  4. Cupala S, Begun A, Merchant R, Barac D, Saliba H (2007) Mapping property hierarchies to schemas. Microsoft Corporation, US Patent 20070061706 A1

  5. Følstad A, Hornbæk K, Ulleberg P (2013) Social design feedback: evaluations with users in online ad-hoc groups. Hum-Centric Comput Inf Sci 3:18

    Article  Google Scholar 

  6. Gardner B, Martin K (1994) HRFT measurements of a KEMAR dummy-head microphone. MIT Media Lab Percept Comput Tech Rep. http://sound.media.mit.edu/resources/KEMAR.html

  7. Goto M, Hashiguchi H, Nishimura T, Oka R (2003) RWC music database: music genre database and musical instrument sound database. In: Proceedings of the 4th International Conference on Music Information Retrieval (ISMIR 2003), pp 229–230, October 2003

  8. Gribonval R, Benaroya L, Vincent E, Fevotte C (2003) Proposal for performance measurement in source separation. In: 4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA2003), April 2003, Nara, Japan

  9. Gupta N, Barreto A, Joshi M, Agudelo JC (2010) HRTF database at FIU DSP lab. ICASSP. doi:10.1109/ICASSP.2010.5496084

  10. Huang YP, Lai SL (2012) Novel query-by-humming/singing method with fuzzy inference system. Journal of Convergence 3(4):1–8

  11. Jeub M, Schafer M, Vary P (2009) A binaural room impulse response database for the evaluation of derveration algorithms. Inst Commun Syst Data Process IEEE. doi:10.1109/ICDSP.2009.5201259

  12. Jot J-M (1992) An analysis/synthesis approach to real-time artificial reverberation. Studer Digitec S.A, France Telecom Paris 2:221–224

  13. Lee S, Choi G, Kim S (2005) A method of the cross-talk cancellation for an sound reproduction of 5.1 channel speaker system. Inst Electron Inf Eng 42:159–166

    Google Scholar 

  14. Macnamara J (2010) Remodelling media: the urgent search for new media business models. Media Int Aust Inc Cult Policy Issue 137:20–35

  15. Nakamura S, Hiyane K, Asno F, Nishiura T, Yamada T (2000) Acoustical sound database in real environments for sound scene understanding and hands-free speech recognition. In: Proc. of LREC, pp 965–968

  16. Ng CK, Fam JG, Ee GK, Noordin NK (2013) Finger triggered virtual musical instruments. J Converg 4(1):39–46

  17. Rabiner LR, Juang BH (1986) An introduction to hidden Markov models. IEEE ASSP Mag 3(1):4–16

  18. Reshef D, Reshef Y, Finucane H, Grossman S, McVean G, Turnbaugh P, Lander E, Mitzenmacher M, Sabeti P (2011) Detecting novel associations in large datasets. Science 334(6062):1518–1524

  19. Silla CN Jr., Koerich AL, Kaestner CAA (2002) The latin music database. http://ismir2008.ismir.net/papers/ISMIR2008_106.pdf

  20. Stewart R, Sandler M (2010) Database of omnidirectional and b-format room impulse responses. In: Proc. of IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP 2010), Dallas, Texas, March 2010

  21. Vincent E, Gribonval R, Fevotte C (2006) Performance measurement in blind audio source separation. IEEE Trans Audio Lang Process 14:1462–1469

    Article  Google Scholar 

  22. Vincent E, Sawada H, Bofill P, Makino S, Rosca JP (2007) First stereo audio source separation evaluation campaign: data, algorithms and results. In Proc. Int. Conf. on Independent Component Analysis and Signal Separation 552–559

  23. Wen JYC, Gaubitch ND, Habets EAP, Myatt T, Naylor PA (2006) Evaluation of speech dereverberation algorithms using the MARDY database. In International Workshop on Acoustic Echoand Noise Control, Paris, France

  24. Zhu C, Zhu Q, Zuzarte C, Ma W (2013) Developing a dynamic materialized view index for efficiently discovering usable views for progressive queries. J Inf Process Syst 9(4):511–537

    Article  Google Scholar 

Download references

Acknowledgments

“This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (NIPA-2013-H0301-13-4005) supervised by the NIPA (National IT Industry Promotion Agency)”

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sanggil Kang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kang, S., Hwang, J., Kim, J. et al. Design of database for evaluating 3D audio core algorithms. Multimed Tools Appl 75, 14181–14196 (2016). https://doi.org/10.1007/s11042-015-2679-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-015-2679-1

Keywords

Navigation