Vol. 48 No. 3 Mar Evaluation of Music-noise Assimilation Playback for Portable Audio Players Akifumi Inoue, Shohei Bise, Satoshi Ichimura and

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1 Vol. 48 No. 3 Mar Evaluation of Music-noise Assimilation Playback for Portable Audio Players Akifumi Inoue, Shohei Bise, Satoshi Ichimura and Yutaka Matsushita Though the population of portable audio listeners keeps growing, it still carries issues such as distractive background noise. This paper proposes a background noise reduction method using knowledge obtained by musical instrument performances. The method is based on our experience that listening to music feels comfortable when the rhythm accents are matched up at the correct timing. In our method, noise with a periodic rhythm takes the role of the rhythm section such as drums and basses. Then the tempo of the current track is converted at an unnoticeable amount so that the accents of the track can synchronize with that of the noise. We examined the reduction effects by carrying out five experiments, in which the traveling sound of a train was set as the periodical noise. Results of the experiments showed that the noise was faded out to a pleasant level without carrying out any spectrum noise reduction. We also showed that unreasonable changes in the tempo were unnecessary to keep an constant effectiveness ) School of Computer Science, Tokyo University of Technology ALICE FORUM

2 1252 Mar beatmania (a) 2) 1(b) 1(c) DJ 2001

3 Vol. 48 No Fig. 1 Noise effects on melody line. Fig. 2 2 Overview of the proposed method BPM: Beat Per Minute BPM (1) (2) 2 3 Fig. 3 System flow. 2 2(a) BPM BPM 2(b) BPM BPM BPM BPM BPM

1254 Mar. 2007 BPM 3.4 250 4,000 khz 0.2% TSM Time Scale Modification BPM 2 DJ Disk Jockey DJ 3) ±10% 4. Windows Visual C++ WAVE 44.1 khz 16 bit1 1 3 4 4 5 4 Fig. 4 HPF for train noise. 5 Fig.

4 1254 Mar BPM ,000 khz 0.2% TSM Time Scale Modification BPM 2 DJ Disk Jockey DJ 3) ±10% 4. Windows Visual C++ WAVE 44.1 khz 16 bit Fig. 4 HPF for train noise. 5 Fig. 5 The waveform of filtered noise. 1 Table 1 SOLA Parameters for SOLA. α 0.9 <α<1.1 S a 2,000 / α S s 2,000 k min 400 k max 400 N 2,800 BPM 65 4),5) BPM TSM SOLA Synchronous OverLap and Add 6) SOLA 7) OLA SOLA α S a S s k min k max N 8) 1 α Screen-

Vol. 48 No. 3 1255 6 Fig. 6 Amplitudes of music and noise after the synchronization. blast Movie Studio BPM 5. 5.1 20 / / 5 7 150 Hz 2,000 4,000 Hz 200 Hz 2,000 Hz 11,000 Hz 20 0 0.015 7 Fig.

5 Vol. 48 No Fig. 6 Amplitudes of music and noise after the synchronization. blast Movie Studio BPM / / Hz 2,000 4,000 Hz 200 Hz 2,000 Hz 11,000 Hz Fig. 7 Frequency characteristics of noise and music-beats. 1 A BPM B A B BPM A B dB BPM BPM 1 C 1 D 3 C D BPM C D C: BPM=65 D: BPM= BPM 120 BPM 60 2

6 1256 Mar Fig. 8 Test 1 (availability). Fig. 11 Test 4 (back-beat). 9 2 Fig. 9 Test 2 (noise resistance) Fig. 12 Test 5 (temporal characteristic). I 12 I 9) 10 3 BPM Fig. 10 Test 3 (The case where BPM difference between music and noise is larger). E F 3 3 E F E F BPM: I / 10) A 1 BPM B 4 A: 1.60 B: 3.55 B

7 Vol. 48 No Fig. 13 The result of test Fig. 15 The result of test Fig. 14 The result of test A B A: 10 db B: 7dB A 3 C 6 5 D 9 D C D BPM 4 E 7 8 F 5 3 ID I ),12) 7

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9 Vol. 48 No BPM 1 BGM 7. 4) 5) 14) ) 16 1) Schafer, R.M. (1996). 2) (2000). 3) 2006-GN-058 pp (2006). 4)

1260 Mar. 2007 2003- MUS-53 pp.55 60 (2003). 5) 2004-MUS-56 pp.49 56 (2004). 6) Roucos, S. and Wilgus, A.M.: High Quality Time-Scame Modification for Speech, IEEE International Conference on ICASSP 85, Vol.

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10 1260 Mar MUS-53 pp (2003). 5) 2004-MUS-56 pp (2004). 6) Roucos, S. and Wilgus, A.M.: High Quality Time-Scame Modification for Speech, IEEE International Conference on ICASSP 85, Vol.10, pp (1985). 7) Wong, J.W., Au, O.C. and Wong, P.H.: Fast Time Scale Modification using Envelope- Matching Technique (EM-TSM), IEEE International Symposium on ISCAS 98, Vol.5, pp (1998). 8) C MAGAZINE, Vol.3, pp (2002). 9) 1 (1990). 10) Massaro, D.: Preperceptual images, processing time and perceptual units in auditory perception, Psychological Review, Vol.79, No.2, pp (1972). 11) pp.h 93 78, MA93 31 (1993). 12) 7 pp (1995). 13) Moore, B. (1994). 14) Vol.J77- D-II, No.5, pp (1994). 15) Vol.3, No.1, pp (2004) ACM IT TEXT Web IT TEXT Web DICOMO ACM ( ) ( )

11 Vol. 48 No MIS ITS LAN 201x VR IEEE ACM

& Vol.5 No (Oct. 2015) TV 1,2,a) , Augmented TV TV AR Augmented Reality 3DCG TV Estimation of TV Screen Position and Ro

& Vol.5 No (Oct. 2015) TV 1,2,a) , Augmented TV TV AR Augmented Reality 3DCG TV Estimation of TV Screen Position and Ro TV 1,2,a) 1 2 2015 1 26, 2015 5 21 Augmented TV TV AR Augmented Reality 3DCG TV Estimation of TV Screen Position and Rotation Using Mobile Device Hiroyuki Kawakita 1,2,a) Toshio Nakagawa 1 Makoto Sato