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Next: Improvements to previous model Up: Auditory sound segregation model Previous: Grouping block

Separation block

The separation block determines Ak(t), Bk(t), $\theta_{1k}(t)$, and $\theta_{2k}(t)$ from Sk(t) and $\phi_k(t)$ using constraints (ii) and (iv) in the determined concurrent time-frequency region, as shown in Fig. 2 [Unoki and Akagi1999b].

Constraint (ii) is implemented such that Ck,R(t) and Dk,R(t) are linear (R=1) piecewise-differentiable polynomials in order to reduce the computational cost of estimating Ck,R(t) and Dk,R(t). In this assumption, Ak(t) and $\theta_{1k}(t)$, which can be allowed to undergo a temporal change, constrain the second-order polynomials ( $A_k(t)=\int C_{k,1}(t)dt+C_{k,0}'$ and $\theta_{1k}(t)=\int D_{k,1}(t)+D_{k,0}'$).

In the segment Th-Th-1 that can be determined by E0,R(t)=0, the terms Ak(t), Bk(t), $\theta_{1k}(t)$, and $\theta_{2k}(t)$ are determined by the following steps. First, the estimation regions, $\hat{C}_{k,0}(t)-P_k(t) \leq C_{k,1}(t) \leq \hat{C}_{k,0}(t)+P_k(t)$ and $\hat{D}_{k,0}(t)-Q_k(t) \leq D_{k,1}(t) \leq \hat{D}_{k,0}(t)+Q_k(t)$, are determined by using the Kalman filter, where $\hat{C}_{k,0}(t)$ and $\hat{D}_{k,0}(t)$ are the estimated values and Pk(t) and Qk(t) are the estimated errors (See Appendix A). Next, the candidates of Ck,1(t) at any Dk,1(t) are selected by using the spline interpolation in the estimated error region [Unoki and Akagi1999a]. Then, $\hat{C}_{k,1}(t)$ is determined by using

 \begin{displaymath}\hat{C}_{k,1}=\mathop{\arg\max}_{\hat{C}_{k,0}-P_k\leq C_{k,1...
...\vert\hat{A}_k\vert\vert \vert\vert\hat{\hat{A}}_k\vert\vert},
\end{displaymath} (10)

where $\hat{A}_k(t)$ is obtained by the spline interpolation and $\hat{\hat{A}}_k(t)$ is determined in the across-channel that satisfies constraint (iii). Finally, $\hat{D}_{k,1}(t)$ is determined by using

 \begin{displaymath}\hat{D}_{k,1}=\mathop{\arg\max}_{\hat{D}_{k,0}-Q_k\leq D_{k,1...
...\vert\hat{A}_k\vert\vert \vert\vert\hat{\hat{A}}_k\vert\vert}.
\end{displaymath} (11)

Since, $\theta_k(t)$ is determined by

 \begin{displaymath}\theta_k(t)=\arctan\left(\frac{S_k(t)\sin(\phi_k(t)-\theta_{1k}(t))}{S_k(t)\cos(\phi_k(t)-\theta_{1k}(t))+C_k(t)}\right),
\end{displaymath} (12)

where $C_k(t)=-\int C_{k,R}(t)dt-C_{k,0}=-A_k(t)$ [Unoki and Akagi1999a], and $\theta_{1k}(t)$ is determined from $\hat{D}_{k,1}(t)$, the terms Ak(t), Bk(t), and $\theta_{2k}(t)$ can be determined from Eq. (4), Eq. (5), and $\theta_{2k}(t)=\theta_k(t)+\theta_{1k}(t)$, respectively.


next up previous
Next: Improvements to previous model Up: Auditory sound segregation model Previous: Grouping block
Masashi Unoki
2000-11-07