Huge music archives on mobile devices: toward an automated dynamic organization

Publikation: Bidrag til tidsskriftTidsskriftartikelfagfællebedømt

Standard

Huge music archives on mobile devices : toward an automated dynamic organization. / Blume, H.; Bischl, B.; Botteck, M.; Igel, Christian; Martin, R.; Rötter, G.; Rudolph, G.; Theimer, W.; Vatolkin, I.; Weihs, C.

I: IEEE Signal Processing Magazine, Bind 28, Nr. 4, 2011, s. 24-39.

Publikation: Bidrag til tidsskriftTidsskriftartikelfagfællebedømt

Harvard

Blume, H, Bischl, B, Botteck, M, Igel, C, Martin, R, Rötter, G, Rudolph, G, Theimer, W, Vatolkin, I & Weihs, C 2011, 'Huge music archives on mobile devices: toward an automated dynamic organization', IEEE Signal Processing Magazine, bind 28, nr. 4, s. 24-39. https://doi.org/10.1109/MSP.2011.940880

APA

Blume, H., Bischl, B., Botteck, M., Igel, C., Martin, R., Rötter, G., Rudolph, G., Theimer, W., Vatolkin, I., & Weihs, C. (2011). Huge music archives on mobile devices: toward an automated dynamic organization. IEEE Signal Processing Magazine, 28(4), 24-39. https://doi.org/10.1109/MSP.2011.940880

Vancouver

Blume H, Bischl B, Botteck M, Igel C, Martin R, Rötter G o.a. Huge music archives on mobile devices: toward an automated dynamic organization. IEEE Signal Processing Magazine. 2011;28(4):24-39. https://doi.org/10.1109/MSP.2011.940880

Author

Blume, H. ; Bischl, B. ; Botteck, M. ; Igel, Christian ; Martin, R. ; Rötter, G. ; Rudolph, G. ; Theimer, W. ; Vatolkin, I. ; Weihs, C. / Huge music archives on mobile devices : toward an automated dynamic organization. I: IEEE Signal Processing Magazine. 2011 ; Bind 28, Nr. 4. s. 24-39.

Bibtex

@article{494418305f814577a342254ced0f590f,
title = "Huge music archives on mobile devices: toward an automated dynamic organization",
abstract = "The availability of huge nonvolatile storage capacities such as flash memory allows large music archives to be maintained even in mobile devices. With the increase in size, manual organization of these archives and manual search for specific music becomes very inconvenient. Automated dynamic organization enables an attractive new class of applications for managing ever-increasing music databases. For these types of applications, extraction of music features as well as subsequent feature processing and music classification have to be performed. However, these are computationally intensive tasks and difficult to tackle on mobile platforms. Against this background, we provided an overview of algorithms for music classification as well as their computation times and other hardware-related aspects, such as power consumption on various hardware architectures. For mobile platforms such as smartphones, a careful balance of algorithm complexity, hardware architecture, and classification accuracy has to be found to provide a high quality user experience. ",
author = "H. Blume and B. Bischl and M. Botteck and Christian Igel and R. Martin and G. R{\"o}tter and G. Rudolph and W. Theimer and I. Vatolkin and C. Weihs",
year = "2011",
doi = "10.1109/MSP.2011.940880",
language = "English",
volume = "28",
pages = "24--39",
journal = "I E E E - Signal Processing Magazine",
issn = "1053-5888",
publisher = "I E E E",
number = "4",

}

RIS

TY - JOUR

T1 - Huge music archives on mobile devices

T2 - toward an automated dynamic organization

AU - Blume, H.

AU - Bischl, B.

AU - Botteck, M.

AU - Igel, Christian

AU - Martin, R.

AU - Rötter, G.

AU - Rudolph, G.

AU - Theimer, W.

AU - Vatolkin, I.

AU - Weihs, C.

PY - 2011

Y1 - 2011

N2 - The availability of huge nonvolatile storage capacities such as flash memory allows large music archives to be maintained even in mobile devices. With the increase in size, manual organization of these archives and manual search for specific music becomes very inconvenient. Automated dynamic organization enables an attractive new class of applications for managing ever-increasing music databases. For these types of applications, extraction of music features as well as subsequent feature processing and music classification have to be performed. However, these are computationally intensive tasks and difficult to tackle on mobile platforms. Against this background, we provided an overview of algorithms for music classification as well as their computation times and other hardware-related aspects, such as power consumption on various hardware architectures. For mobile platforms such as smartphones, a careful balance of algorithm complexity, hardware architecture, and classification accuracy has to be found to provide a high quality user experience.

AB - The availability of huge nonvolatile storage capacities such as flash memory allows large music archives to be maintained even in mobile devices. With the increase in size, manual organization of these archives and manual search for specific music becomes very inconvenient. Automated dynamic organization enables an attractive new class of applications for managing ever-increasing music databases. For these types of applications, extraction of music features as well as subsequent feature processing and music classification have to be performed. However, these are computationally intensive tasks and difficult to tackle on mobile platforms. Against this background, we provided an overview of algorithms for music classification as well as their computation times and other hardware-related aspects, such as power consumption on various hardware architectures. For mobile platforms such as smartphones, a careful balance of algorithm complexity, hardware architecture, and classification accuracy has to be found to provide a high quality user experience.

U2 - 10.1109/MSP.2011.940880

DO - 10.1109/MSP.2011.940880

M3 - Journal article

VL - 28

SP - 24

EP - 39

JO - I E E E - Signal Processing Magazine

JF - I E E E - Signal Processing Magazine

SN - 1053-5888

IS - 4

ER -

ID: 32647598