MIDI [8] MIDI. [9] Hsu [1], [2] [10] Salamon [11] [5] Song [6] Sony, Minato, Tokyo , Japan a) b)

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1 1,a) 1,b) 1,c) 1. MIDI [1], [2] U/D/S 3 [3], [4] 1 [5] Song [6] 1 Sony, Minato, Tokyo , Japan a) Emiru.Tsunoo@jp.sony.com b) AkiraB.Inoue@jp.sony.com c) Masayuki.Nishiguchi@jp.sony.com MIDI [7] Li HMM Viterbi [8] [9] Hsu [10] Salamon [11] c 2013 Information Processing Society of Japan 1

2 [9] (a) 2-(a) 2-(b) 0 1 x y Y (x, y) 1 x X 1 y Y {a 0, a 1,..., a K 1 } l(x, y) = K 1 k=0 a k log Y (x, y) (1) v(x, y) = 1 (µ(x)<u Y (x,y)<l(x,y)) 0 (U Y (x,y) µ(x)) l(x, y) µ(x) U Y (x, y) µ(x) (otherwise) (2) µ(x) x log Y (x, y) U Y (x, y) y p (y) p + (y) P (x, y) = log Y (x, p (y)) P + (x, y) = log Y (x, p + (y)) U Y (x, y) = (p +(y) y)p (x, y) + (y p (y))p + (x, y) p + (y) p (y) (3) p Y (x, p) = max Y (x, j) (4) p H j p+h c 2013 Information Processing Society of Japan 2

3 2 : (a) (b) (a) (c) U(x, y) (d) v(x, y) (e) S(x, y) H U Y (x, y) 2-(c) v(x, y) 2-(d) v(x, y) Barry 2 [12] [7], [11] Barry A i,c (x, y) N v(x, ny) Y L (x, ny) βiy R (x, ny) A i,0 (x, y) = A i,1 (x, y) = n=1 N α (5) N v(x, ny) Y R (x, ny) βiy L (x, ny) n=1 N α (6) N α Y L (x, y) Y R (x, y) 3 The Beatles Hey Jude S(x, y) : (a) S(x, y) (b) T (x) (c) S(x, y) (d) β i 0 β i 1 S(x, y) = max A i,c(x, y) min A i,c(x, y) (7) i,c i,c 2 S(x, y) 2-(e) S(x, y) The Beatles Hey Jude S(x, y) 3-(a) Y R (x, y) 0 S (x, y) = 1 N α N v(x, ny) Y L (x, ny) (8) n=1 c 2013 Information Processing Society of Japan 3

4 4 2.3 S(x, y) 3 (4) S(x, y) 4 S(x, y) T 1 F 1 F 2 2 1/12 F 2/F 1 2 1/12 5 T 2 3-(a) 3-(c) Viterbi [8], [10] [8] T (x) S(x, y) 5 c t 1 c t 4 [8] 3-(a) 3-(b) U m = {(x m,1, y m,1 ), (x m,2, y m,2 ),...} x m,1 = x m,2 1 = x m, m U m m M U m x m,first = x m,1 x m,last x m,last < x n,first, (m < n, m, n M) D M D M = ( m M (x,y) U m S(x, y) γ 1 (x,y) U m log y log T (x) γ 2 log y m,last log y m,first ) (9) m m γ 1 γ 2 (9) c t 1 c t 4 M c t 1 c t 2 2 D L Y X d L (x, y) D E Y 1 d E (y) d E (0) = 0 (10) d L (0, y) = S(0, y) + γ 1 log y log T (0) (11) if (x.y) U m and x = x m,first then { de (j) + S(x, y) γ 1 log y log T (x) d L (x, y) max j γ 2 log j log y } c 2013 Information Processing Society of Japan 4

5 (12) if (x, y) U m and x = x m,last then { de (y) d E (y) max d L (x 1, y) + S(x, y) γ1 log y log T (x) 1 ADC2004 1/2 Pop Daisy Opera Jazz MIDI Proposed MIDI (13) if (x, y) U m and x m,first < x < x m,last then d L (x m,n, y m,n ) d L(x m,n 1, y m,n 1 ) + S(x m,n, y m,n ) γ 1 log(y m,n ) log T (x m,n ) D M D Mmax (14) = max d E (j), (15) j D Mmax 3-(c) 3-(d) 3. Zhu [2] [2] Hz (4) H 16 (9) γ 1 γ (5) α 0.5 a k 0.15π 2 ADC Pop Daisy Opera Jazz MIDI Proposed MIDI MIREX *1 MIREX Raw Pitch Accuracy 1/2 50 MIREX ADC Pop Daisy Opera Jazz, MIDI 5 MIREX MELODIA[11] 1 Jazz MIDI Pop Daisy Opera 1/2 1 2 Opera *1 Music Information Retrieval Evaluation exchange (MIREX) [Online]. Melody Extraction c 2013 Information Processing Society of Japan 5

6 3 MIDI 1000 Reference Melody Top 1 Top 5 Top 10 MIDI 100 % 100 % 100 % MELODIA % % % Proposed (Monaural) % % % Proposed (Stereo) % % % Reference Melody Top 1 Top 5 Top 10 MIDI % % % MELODIA % % % Proposed (Monaural) % % % Proposed (Stereo) % % % 4.2 MIDI MELODIA MIDI 1000 MIDI Top 1 Top 5 5 Top MELODIA MIDI 4 MIDI 5. 3 [1] S. Pauws, CubyHum: a fully operational query by humming system, in Proc. ISMIR, pp , [2] Y. Zhu and D. Shasha, Warping indexes with envelope transform for query by humming, in ACM SIGMOD Int. Conf., pp , [3] A. Ghias, J. Logan, D. Chamberlin, and B. Smith, Query by humming: musical information retrieval in an audio database, in Proc. ACM Multimedia, pp , [4] L. Lu, H. You, and H.-J. Zhang, A new approach to query by humming in music retrieval, in Proc. ICME, pp.22-25, [5] T. Nishimura, H. Hashiguchi, J. Takita, J. X. Zhang, M. Goto and R. Oka, Music signal spotting retrieval by a humming query using start frame feature dependent continuous dynamic programming, in Proc. ISMIR, pp , [6] J. Song, S. Y. Bae, and K. Yoon, Mid-level music melody representation of polyphonic audio for query-byhumming system, in Proc. ISMIR, pp , [7] M. Goto, A real-time music-scene-description system: predominant-f0 estimation for detecting melody and bass line in real-world audio signals, in Speech Communication, vol. 43, no. 4, pp , [8] Y. Li, D. L. Wang, Separation of singing voice from music accompaniment for monaural recordings, in Trans. Audio, Speech and Language Processing, vol. 15, no. 4, pp , [9] H. Tachibana, T. Ono, N. Ono, and S. Sagayama, Melody line estimation in homophonic music audio signals based on temporal-variablity of melody source, in Proc. ICASSP, pp , [10] C. L. Hsu, D. L. Wang, and J.-S. R. Jang, A trend estimation algorithm for singing pitch detection in musical recordings, in Proc. ICASSP, pp , [11] J. Salamon and E. Goméz, Melody extraction from polyphonic music signals using pitch contour characteristic, in Trans. Audio, Speech and Language Processing, vol. 20, no. 6, pp , [12] D. Barry, B. Lawlor, and E. Coyle, Sound source separation: Azimuth discrimination and resynthesis, in Proc. Int. Conf. Digital Audio Effects, [13] R. B. Dannenberg and N. Hu, Understanding search performance in query-by-humming systems, in Proc. ISMIR, pp , c 2013 Information Processing Society of Japan 6

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