Exact(6)
We have applied the GS, GA and PSO techniques for optimizing the integration weight factor.
The final solution gives the integration weight scale factor for the score level fusion [34].
In this approach, the integration weight is determined from the relative reliability of the two modalities.
In order to emphasize or de-emphasize the scores obtained from the unimodal systems, the integration weight factor must be adaptive and optimal.
Even though the integration weight using Equation 22 can improve noise robustness under certain noise conditions, it is not always the optimal.
alpha_{kl} = frac{{alpha_{0} (left| {x_{k} - x_{l} } right|)}}{{sumlimits_{m = 1}^{N} {w_{m} alpha_{0} (left| {x_{k} - x_{m} } right|)} }} (10 where ( w_{l} ) is the integration weight of the integration point number l, and the value of which is 1 as single integration point is used for all the beam elements.
Similar(54)
The integration weights are estimated in such a way that it maximizes the recognition accuracy.
The 'optimal integration weights' thus obtained in the training stage are used as the integration weights for fusion in the testing stage. .
Lewis et al. shed some light on audio-visual speech recognition systems using dispersion measures as the integration weights [16].
The calculation of spherical harmonic expansion coefficients requires integration over the full sphere and can be a computationally cumbersome and also numerically sensitive (with respect to the integration weights) procedure.
The relative ancillary ratio estimates of the two modalities and the optimal integration weight β estimated under various noise conditions are presented in Table 1.
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