第22回 ロボット聴覚特集 - 奥乃研究室 - 京都大学

1 () 2 SIMO-ICA 3 SIMO-ICA tele-presence SIMO-ICA head and torso simulator (HATS) SIMO-ICA , (ITD) (ILD) SIMO-ICA .2 BSS 2.1 , K 2, L 2 . .x(t) ===N−1∑a(n)s(t − n) =A(z)s(t)n=0[][ ]A 11 (z) A 12 (z) s 1 (t)[A 21 (z) A 22 (z) s 2 (t)]A 11 (z)s 1 (t)+A 12 (z)s 2 (t)A 21 (z)s 1 (t)+A 22 (z)s 2 (t), a(n) =[a kl (n)] kl N , A(z) =[A kl (z)] kl =[ ∑ N−1n=0 a kl(n)z −n ] kl a(n) Z . , z −1 z −n · s(t) =s(t − n) [X] ij i j X 2.2 ICA BSS (1), FIR ICA s1(t)s2(t)A11(z)A22(z)A12(z)A21(z)x1(t)x2(t)Head of Humanoid robotICAB1(z)=A11(z), A21(z)B1(z)s1(t)B2(z)s2(t)DistortedmonauralsignalsB2(z)=A12(z), A22(z)Figure 1: ICA B l (z)(B l (z) ̸=A kl (z)) FIR , . ICA.y(t) =[y 1 (t),y 2 (t)] T =D−1∑n=0w(n)x(t − n), (2), w(n) , D . y(t) y l (t) Kullback-Leibler divergence (KLD) . Choi et al. [16].D−1∑{w [j+1] (n) = w [j] (n)− α off-diagd=0y [j] (t − n + d) T〉 t〈ϕ(y [j] (t))}w [j] (d), (3), α , [j] 〈·〉 t . off-diag X X ϕ(y(t)) =[ϕ(y 1 (t)),ϕ(y 2 (t))] T [tanh(y 1 (t)), tanh(y 2 (t))] T ICA , 2 .• • , . SIMO , K()× L() , , L . ICA s i (t) , b i (n) B i (z)s i (t) 10