A closer look at deep learning neural networks with low-level spectral periodicity features

4th International Workshop on Cognitive Information Processing - Proceedings of CIP 2014

Volumn , Issue , 2014, Pages

  Sturm, Bob L ^a   Kereliuk, Corey ^a   Pikrakis, Aggelos ^b  

^a AALBORG UNIVERSITY   (Denmark)

^b UNIVERSITY OF PIRAEUS   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

AUDIO SYSTEMS; CLASSIFICATION (OF INFORMATION);

BENCHMARK DATASETS; DEEP LEARNING; FIGURE OF MERITS; GENRE CLASSIFICATION; GROUND TRUTH; MUSIC GENRE; TIME STRETCHING;

DATA PROCESSING;

EID: 84904663146     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIP.2014.6844511     Document Type: Conference Paper

References (12)

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3. A. Pikrakis, I. Antonopoulos, and S. Theodoridis, "Music meter and tempo tracking from raw polyphonic audio" in Proc. ISMIR, 2004.
4. B. L. Sturm, "Classification accuracy is not enough: On the evaluation of music genre recognition systems" J. Intell. Info. Systems, vol. 41, no. 3, pp. 371-406, 2013.
5. B. L. Sturm, "Making explicit the formalism underlying evaluation in music information retrieval research: A look at the MIREX automatic mood classification task" in Post-proceedings of the 2013 Computer Music Modeling and Research, 2014.
6. B. L. Sturm, "Evaluating music emotion recognition: Lessons from music genre recognition?" in Proc. ICME, 2013, pp. 1-6.
7. B. L. Sturm, "A simple method to determine if a music information retrieval system is a "horse'" (submitted), 2014.
8. B. L. Sturm, "The state of the art ten years after a state of the art: Future research in music information retrieval" J. New Music Research (in press), 2014.
9. O. Pfungst, Clever Hans (The horse of Mr. Von Osten): A contribution to experimental animal and human psychology, Henry Holt, New York, 1911.
10. F. Gouyon, S. Dixon, E. Pampalk, and G. Widmer, "Evaluating rhythmic descriptors for musical genre classification" in Proc. Int. Audio Eng. Soc. Conf., 2004, pp. 196-204.
11. F. Krebs, S. Boch, and G. Widmer, "Rhythmic pattern modeling for beat and downbeat tracking in musical audio" in Proc. ISMIR, 2013.
12. F. Gouyon and S. Dixon, "Dance music classification: A tempo-based approach" in Proc. ISMIR, 2004, pp. 501-504.