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R ESEARCH P ROGRESS R EPORT – C OVER S ONGS I DENTIFICATION 2015.11.25 Ken.

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Presentation on theme: "R ESEARCH P ROGRESS R EPORT – C OVER S ONGS I DENTIFICATION 2015.11.25 Ken."— Presentation transcript:

1 R ESEARCH P ROGRESS R EPORT – C OVER S ONGS I DENTIFICATION 2015.11.25 Ken

2 2/22 Outline Introduction Surveys Progress

3 3/22 Introduction What is “cover songs identification”?

4 4/22 Introduction (Cont’d) Another example:

5 5/22 Introduction (Cont’d) Definition : In popular music, a cover version or cover song, or simply cover, is a new performance or recording of a previously recorded, commercially released song by someone other than the original artist or composer Issues: In different cover versions, there exists different Language Background (Companion) Music Singer Tones Etc.

6 6/22 Surveys Related papers: [Cover Songs Identification] Justin Salamon, Joan Serr`a, Emilia G´omez, “Tonal Representations for Music Retrieval: From VersionIdentification to Query-by- Humming”, International Journal of Multimedia Information Retrieval (MMIR), 2012 [Melody/Bass Line Extraction] Justin Salamon., Emilia G´omez, “Melody extraction from polyphonicmusic signals using pitch contour characteristics”, IEEE Transactions on Audio, Speech, and Language Processing, 2012 [Harmonic Extraction] Emilia G´omez, “Tonal description of music audio signals”, Ph.D. thesis, Universitat Pompeu Fabra, Barcelona, Spain, 2006 [Harmonic Extraction] Joan Serr`a, Emilia G´omez, Perfecto Herrera and Xavier Serra, “Chroma Binary Similarity and Local Alignment Applied to Cover Song Identification”, IEEE Transactions on Audio, Speech, and Language Processing, 2008 [Qmax/Similarity] Joan Serr`a, Xavier Serra, Andrzejak R.G, “Cross recurrence quantification for cover song identification”, New Journal of Physics, 2009

7 7/22 Surveys (Cont’d) System flowchart:

8 8/22 Surveys (Cont’d) Melody/Bass Line representations:

9 9/22 Surveys (Cont’d) Harmonic Pitch Class Profiles (HPCP):

10 10/22 Surveys (Cont’d) (Dis)Similarity method: Qmax Under construction!

11 11/22 Surveys (Cont’d) Evaluation metrics: Mean Average Precision (MAP) Mean averaged Reciprocal Rank (MaRR) aRR1 = (1+1/3+1/6+1/9+1/10)/5 = 0.342 aRR2 = (1/2+1/5+1/7)/3 = 0.281 MaRR = (0.342+0.281)/2 = 0.312

12 12/22 Surveys (Cont’d) Evaluation Results: 2125 songs include 523 version sets (Avg. 4 songs/version) 76 songs for parameter training (subset of 2125 songs)

13 13/22 Surveys (Cont’d)

14 14/22 Progress Undergoing: Collect dataset Extract melody by Lambert’s MIREX submission Implement HPCP/Qmax if needed Compare with DTW


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