https://oldena.lpnu.ua/handle/ntb/52455| Title: | Music Content Selection Automation |
| Authors: | Gladkykh, Tetiana Hnot, Taras Grubnyk, Roman |
| Affiliation: | Data Science Group, SoftServe |
| Bibliographic description (Ukraine): | Gladkykh T. Music Content Selection Automation / Tetiana Gladkykh, Taras Hnot, Roman Grubnyk // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Львів : Lviv Politechnic Publishing House, 2018. — P. 599–604. — (Machine Vision and Pattern Recognition). |
| Bibliographic description (International): | Gladkykh T. Music Content Selection Automation / Tetiana Gladkykh, Taras Hnot, Roman Grubnyk // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Lviv Politechnic Publishing House, 2018. — P. 599–604. — (Machine Vision and Pattern Recognition). |
| Is part of: | Data stream mining and processing : proceedings of the IEEE second international conference, 2018 |
| Conference/Event: | IEEE second international conference "Data stream mining and processing" |
| Issue Date: | 28-Feb-2018 |
| Publisher: | Lviv Politechnic Publishing House |
| Place of the edition/event: | Львів |
| Temporal Coverage: | 21-25 August 2018, Lviv |
| Keywords: | music recommender tracks similarity melspectrogram deep-learning tags recognition |
| Number of pages: | 6 |
| Page range: | 599-604 |
| Start page: | 599 |
| End page: | 604 |
| Abstract: | We are proposing the solution for musical content recommendation, which is based on assessment of tracks similarity with taking into account tree factors - genre description, sound and rhythm patterns and user preferences. We have introduced the music compositions distance measure based on their representation as mel-spectrograms, and deeplearning approach to high-level (tags) music description, based on the extracted acoustic and rhythmic patterns from their spectra. |
| URI: | https://ena.lpnu.ua/handle/ntb/52455 |
| ISBN: | © Національний університет „Львівська політехніка“, 2018 © Національний університет „Львівська політехніка“, 2018 |
| Copyright owner: | © Національний університет “Львівська політехніка”, 2018 |
| URL for reference material: | https://noisey.vice.com/en_us/article/a37x9g/lastfm-was-the-onlymusic-social-network-that-made-sense http://blog.stevekrause.org/2006/01/pandora-and-lastfm-nature-vsnurture-in.html http://www.theserverside.com/feature/How-Pandorabuilt-a-better-recommendation-engine https://yandex.com/company/technologies/disco/ |
| References (Ukraine): | [1] "Shazam Launches Resonate TV Sales Platform," Billboard. 5 August 2014. Retrieved 15 June 2015. [2] Bryan Jacobs, "How Shazam Works To Identify (Nearly) Every Song You Throw at It". Gizmodo. Retrieved 13 June 2017. [3] Elia Alovisi, Last.fm: Was the Only Music Social Network That Made Sense, December, 2017, [https://noisey.vice.com/en_us/article/a37x9g/lastfm-was-the-onlymusic-social-network-that-made-sense] [4] “Pandora and Last.fm: Nature vs. Nurture in Music Recommenders,” Words & Numbers, A blog by Steve Krause, January, 2006 [http://blog.stevekrause.org/2006/01/pandora-and-lastfm-nature-vsnurture-in.html] [5] George Lawton, “How Pandora built a better recommendation engine,” August 2017, [http://www.theserverside.com/feature/How-Pandorabuilt-a-better-recommendation-engine] [6] Recommendation Technology ‘Disco’, [https://yandex.com/company/technologies/disco/] [7] Florian Eyben, Real-time Speech and Music Classification by Large Audio Feature Space Extraction. Springer, 2016. [8] Justin Salamon, “Tonal Representations for Music Retrieval: From Version Identification to Query-by-Humming,” International Journal of Multimedia Information Retrieval, vol. 2, iss. 1, pp 45–58, March 2013. [9] J.,Salamon, and E. Gómez, “Melody Extraction from Polyphonic Music Signals using Pitch Contour Characteristics,” IEEE Transactions on Audio, Speech and Language Processing, vol. 20, iss. 6, pp 1759-1770, 2012. [10] E. Allamanche and B. Froba, “Content-based identification of audio material using mpeg-7 low level description,” In in Proc. of the Int. Symp. of Music Information Retrieval, pp 197–204, 2001. [11] J. Wood and J. Dykes, “Spatially ordered treemaps,” IEEE Transactions on Visualization and Computer Graphics, vol. 14(6), pp. 1348–1355, 2008. [12] J.-J. Aucouturier and F. Pachet, “Music similarity measures: What’s the use?,’ In Proc. Int. Conf. Music Information Retrieval (ISMIR), Paris, pp. 157-163, 2002 [13] B. Logan and A. Salomon,” A music similarity function based on signal analysis,” In Multimedia and Expo,2001. ICME 2001. IEEE International Conference on, pp. 745–748, 2001. [14] Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval. Cambridge University Press. 2008. [15] Anssi Klapuri, "Introduction to Music Transcription," in Signal Processing Methods for Music Transcription, edited by Anssi Klapuri and Manuel Davy, New York: Springer, 2006, pp. 1–20. ISBN 978-0-387-30667-4. [16] Stanley Smith Stevens, John Volkman and Edwin Newman, "A scale for the measurement of the psychological magnitude pitch". Journal of the Acoustical Society of America, vol. 8 (3), pp 185–190,1937. [17] Douglas O'Shaughnessy, Speech communication: human and machine. Addison-Wesley,1987. ISBN 978-0-201-16520-3. [18] W. Dixon Ward, "Musical Perception," In Jerry V. Tobias. Foundations of Modern Auditory Theory. 1. Academic Press. 1970, pp. 405-447. |
| References (International): | [1] "Shazam Launches Resonate TV Sales Platform," Billboard. 5 August 2014. Retrieved 15 June 2015. [2] Bryan Jacobs, "How Shazam Works To Identify (Nearly) Every Song You Throw at It". Gizmodo. Retrieved 13 June 2017. [3] Elia Alovisi, Last.fm: Was the Only Music Social Network That Made Sense, December, 2017, [https://noisey.vice.com/en_us/article/a37x9g/lastfm-was-the-onlymusic-social-network-that-made-sense] [4] "Pandora and Last.fm: Nature vs. Nurture in Music Recommenders," Words & Numbers, A blog by Steve Krause, January, 2006 [http://blog.stevekrause.org/2006/01/pandora-and-lastfm-nature-vsnurture-in.html] [5] George Lawton, "How Pandora built a better recommendation engine," August 2017, [http://www.theserverside.com/feature/How-Pandorabuilt-a-better-recommendation-engine] [6] Recommendation Technology ‘Disco’, [https://yandex.com/company/technologies/disco/] [7] Florian Eyben, Real-time Speech and Music Classification by Large Audio Feature Space Extraction. Springer, 2016. [8] Justin Salamon, "Tonal Representations for Music Retrieval: From Version Identification to Query-by-Humming," International Journal of Multimedia Information Retrieval, vol. 2, iss. 1, pp 45–58, March 2013. [9] J.,Salamon, and E. Gómez, "Melody Extraction from Polyphonic Music Signals using Pitch Contour Characteristics," IEEE Transactions on Audio, Speech and Language Processing, vol. 20, iss. 6, pp 1759-1770, 2012. [10] E. Allamanche and B. Froba, "Content-based identification of audio material using mpeg-7 low level description," In in Proc. of the Int. Symp. of Music Information Retrieval, pp 197–204, 2001. [11] J. Wood and J. Dykes, "Spatially ordered treemaps," IEEE Transactions on Visualization and Computer Graphics, vol. 14(6), pp. 1348–1355, 2008. [12] J.-J. Aucouturier and F. Pachet, "Music similarity measures: What’s the use?,’ In Proc. Int. Conf. Music Information Retrieval (ISMIR), Paris, pp. 157-163, 2002 [13] B. Logan and A. Salomon," A music similarity function based on signal analysis," In Multimedia and Expo,2001. ICME 2001. IEEE International Conference on, pp. 745–748, 2001. [14] Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval. Cambridge University Press. 2008. [15] Anssi Klapuri, "Introduction to Music Transcription," in Signal Processing Methods for Music Transcription, edited by Anssi Klapuri and Manuel Davy, New York: Springer, 2006, pp. 1–20. ISBN 978-0-387-30667-4. [16] Stanley Smith Stevens, John Volkman and Edwin Newman, "A scale for the measurement of the psychological magnitude pitch". Journal of the Acoustical Society of America, vol. 8 (3), pp 185–190,1937. [17] Douglas O'Shaughnessy, Speech communication: human and machine. Addison-Wesley,1987. ISBN 978-0-201-16520-3. [18] W. Dixon Ward, "Musical Perception," In Jerry V. Tobias. Foundations of Modern Auditory Theory. 1. Academic Press. 1970, pp. 405-447. |
| Content type: | Conference Abstract |
| Appears in Collections: | Data stream mining and processing : proceedings of the IEEE second international conference |
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2018_Gladkykh_T-Music_Content_Selection_599-604.pdf | 457.59 kB | Adobe PDF | View/Open | |
| 2018_Gladkykh_T-Music_Content_Selection_599-604__COVER.png | 667.37 kB | image/png | View/Open |
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