1. A method of executing a neural network in a speech recognition system for recognizing speech of an input speech signal organized into a series of frames, comprising: calculating, by means of said neural network, a first and a second likelihood corresponding to a first and a second non-consecutive frame; calculating a distance between said first and second non-consecutive frames; comparing said distance with a predetermined threshold value to evaluate a possibility of skipping at least one run of the neural network; selectively skipping the at least one run of the neural network in correspondence to each frame between said first and said second non-consecutive frames to optimize the neural network when said distance is lower than said threshold value; calculating a likelihood or likelihoods corresponding to each frame between said first and second non-consecutive frames; calculating said distance as a distance between output likelihoods of said neural network; and providing an optimized neural network by outputting the likelihood or likelihoods corresponding to each frame between said first and second non-consecutive frames to a computer readable medium.