The Bush proposal limits the training period to just three months, ruling out not just training programs, but even substance-abuse treatment for welfare recipients who need to be rehabilitated before moving into the world of work.
However, here it is proposed that limiting the training set to high quality data with only the highest confidence from ChEMBL, leads to better performance.
Overfitting on the data, a potential problem, can be avoided by limiting the complexity of the model and by using techniques such as weight decay, training with noise, and limiting the training of the network.
Several solutions have been proposed to improve the recognition for lower bit-rates, starting with limiting the training signal bandwidth, using perceptual linear prediction (PLP) features or adding a controlled amount of noise.
As discussed in [6], traditional automatic speech recognition techniques are unsuitable for impaired speech for several reasons: the amount of training material is limited, the training samples are highly variable, and they are very different from voices corresponding to non-disabled users.
Although a step in the right direction, ICE limited the training to a total of only four hours, far below the contracted for eight hours of specialized training.
A second distinctive feature of the method is that it limits the training set of oligomers.
The practice of limiting the training of critical care physicians to geographically described intensive care units (ICUs) only is questionable.
Nitz et al 17 allowed participants to choose their own exercises for the training program while Bateni 18 limited the training to only three balance games.
However, limiting the training to 25 000 reads leads to a model that is nearly as accurate while requiring <4 min to train.
