第22回ロボット聴覚特集 - 奥乃研究室 - 京都大学

More documents

Recommendations

Info

12]Bd10 [sec8 nerfe6 ifDle4 veLl2 aruar0tenI-2(a)Real impulse responseImpulse responseestimated by SIMO-ICA-90 -60 -30 0Direction of s 1 [deg]12]Bd10 [sec8 nerfe6 ifDle4 veLl2 aruar0tenI-2(b)0 30 60 90Direction of s 2 [deg]Real impulse responseImpulse responseestimated by SIMO-ICAFigure 6: (a) h (ICA)1 (t) h (FC)2 (t) ILD , (b) h (ICA)2 (t) h (FC)1 (t) ILD ]0s-100s[μ-200 ecne-300 rife-400 De-500 imTl-600 rauarte -700In-800(a)-90 -60 -30 0Direction of s 1 [deg]Real impulse responseImpulse responseestimated by SIMO-ICA800]s700s[μ600 ecne500 rife400 De300 imTla200 ruar100 teIn0(b)0 30 60 90Direction of s 2 [deg]Real impulse responseImpulse responseestimated by SIMO-ICAFigure 7: (a) h (ICA)1 (t) h (FC)2 (t) ITD (b) h (ICA)2 (t) h (FC)1 (t) ITD 0-10-20]ge-30 [dn-40 tioa-50 timse-60 AO-70 D-80-90(a)-90 -60 -30 0Direction of s 1 [deg]Real impulse responseImpulse responseestimated by SIMO-ICA908070]ge60 [dn50 tioa40 timse30 AO20 D100(b)0 30 60 90Direction of s 2 [deg]Real impulse responseImpulse responseestimated by SIMO-ICAFigure 8: (a) Figure 7 (a) ITD s 1 (b) Figure 7 (b) ITD s 2 16
社団法人人工知能学会Japanese Society forArtificial Intelligence人工知能学会JSAI Technical ReportSIG-CHallege-0522-3 (10/14)Blind source separation of many sounds in the frequency domain Hiroshi Sawada, Ryo Mukai, Shoko Araki and Shoji Makino NTT NTT Communication Science Laboratories, NTT Corporation{sawada, ryo, shoko, maki}@cslab.kecl.ntt.co.jpAbstractThis paper describes the frequency-domain approachto the blind source separation (BSS) ofconvolutively mixed acoustic signals. The advantageof the frequency-domain approach is that convolutivemixtures in the time domain can be approximatedas multiple simple mixtures in the frequencydomain. However the permutation ambiguityshould be solved to group the frequency componentsof the same source together. This paperpresents effective methods to align the permutationambiguity. Based on the methods, we succeeded inseparating many sources in real-world situations.1 [1] (BSS: Blind Source Separation [2]) (ICA: Independent Component Analysis [3])BSS ICA ICA ICA [4–6] ICA [7–10]ICA permutation [11–16] permutation 2 2 3 6 3 2 N s 1 (t),...,s N (t) M x 1 (t),...,x M (t) N∑ ∑x j (t) = h jk (l)s k (t − l) (1)k=1 lh jk k j BSS N M N M [16] M 17
Page 4: SCOT(Smoothed Coherence Transform)P
Page 8 and 9: Particle (a)(b)φ12(τ )[14]x ( t )
Page 10 and 11: - 8 -
Page 12 and 13: 1 () 2 SIMO-ICA 3 SIMO-ICA tele
Page 14: ICAy FCy FCy SIMO-ICAs 1(t)x 1(t)1(
Page 17: [15] Y. Mori, H. Saruwatari, T. Tak
Page 21 and 22: • 音源位置マイク配置
Page 23 and 24: Table 1: 6 : SIR (dB)SIR 1 SIR 2 S
Page 25 and 26: 社団法人人工知能学
Page 27 and 28: SIMO-ICA SIMO Figure 2(a)SIMO-ICA
Page 29 and 30: Binary maskConventional ICAConventi
Page 33 and 34: k lo (l), k c (l), k hi (l) l k c
Page 35 and 36: 5.75 m4.33 mNoise1.15 mUser 40°2.1
Page 38 and 39: おける方法論に関し
Page 40 and 41: Fig.6 は幼児の ABR (Auditory
Page 42 and 43: ンターフェースはスパイ
Page 44 and 45: マイクロホン[ 正面 ][ 左
Page 46 and 47: s(k)Crosstalkn(k)R S(k)X P(k)X R(k)
Page 48 and 49: する隠れマルコフモデル
Page 50 and 51: 123ÙÖ ½ ¾º¾ ´º ½µ ´º
Page 52 and 53: ÌÐ ½ ¿º¾ ÅÎÆÇÂ
Page 54 and 55: ÁÒØÖÒØÓÒÐ ÓÒÖÒ ÓÒ Á
Page 56 and 57: 例えば、同一時間差
Page 58 and 59: いて、θの絶対値が大
Page 60 and 61: Fig.11 にこのシステムの処
Page 62 and 63: 5 , 2 EMIEWFig.1 EMIEW EMIEW 6 ,
Page 64: 0 P th , (14) 4.4 3 4 4 1 , 3
Page 69 and 70:
3.1. 3.2. Fig. 3. The
Page 71 and 72:
4.1. Fig. 5. The time co
Page 73 and 74:
社団法人人工知能学
Page 75 and 76:
modal (m, ), whispery (w, ), aspir
Page 77 and 78:
Aperiodicity rate (APR)TLR (Time-La
Page 79 and 80:
Page 81 and 82:
, À, WDS-BF Ñ À℄·
Page 83 and 84:
Table 1: Localization Error of A Si
Page 85 and 86:
Page 87 and 88:
を行い, 閾値処理を
Page 89 and 90:
4. 音声対話制御実験H
Page 91 and 92:
Page 93 and 94:
3 HLDAMLLR [3] (Useful Information
Page 95 and 96:
Class 10degClass 20degClass 10degCl
Page 97 and 98:
Page 99 and 100:
赤い長方形内 ). 以下
Page 101 and 102:
5.2 音場計測結果(dB SPL)
Page 103 and 104:
Page 105 and 106:
a) 90 b) 90 MFMc) d) MFMe) 9
Page 107 and 108:
(3) MFT Julius 7.1 Figure 4: SIG2
show all

第22回 ロボット聴覚特集 - 奥乃研究室 - 京都大学

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?

第22回ロボット聴覚特集 - 奥乃研究室 - 京都大学