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Here, we develop a MIMO mode adaptation technique combining these two approaches to adapt the precoding mode at the FBSs and improve the system performance.
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Some of them are based on a model adaptation technique.
In the HEQ-MA with mean and variance adaptation approach, we used an SNR-dependent covariance model adaptation technique.
A fast adaptation technique of acoustic models is also proposed.
A local grid adaptation technique is used to increase the grid density where required.
Thus, we develop a mode adaptation approach at the FBSs to achieve better performance.
The simplest form of mode adaptation at the FBSs is to apply binary MA.
We show that allowing for mode adaptation at each FBS improves the system performance when compared with using the same mode across the system, and a simple binary choice at each FBS can nearly achieve the optimum mode-adaptation performance.
Kenny's eigenphone method is a multi-speaker modeling technique rather than a speaker adaptation technique in the usual sense.
To cope with the problem of data sparseness, we use the MLLR adaptation technique.
These results show the effectiveness of our NMF-based speaker adaptation technique.
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