1. A method of adapting a neural network of an automatic speech recognition device, comprising the steps of: providing a neural network comprising an input stage for storing at least one voice signal sample, an intermediate stage and an output stage, said output stage outputting phoneme probabilities; providing a linear stage in said neural network; and training said linear stage by means of an adaptation set, wherein the step of providing said linear stage comprises the step of providing said linear stage after said intermediate stage; wherein the step of training said linear stage comprises training said linear stage so that the phoneme probability of a phoneme belonging to an absent class is equal to the phoneme probability of said phoneme calculated by said neural network before the step of providing a linear stage; and wherein the step of training said linear stage further comprises training said linear stage so that the phoneme probability of the phoneme corresponding to a voice signal sample of said adaptation set is calculated by subtracting the phoneme probabilities of all the phonemes belonging to said absent class from 1.
1. A method of adapting a neural network of an automatic speech recognition device, comprising the steps of: providing a neural network comprising an input stage for storing at least one voice signal sample, an intermediate stage and an output stage, said output stage outputting phoneme probabilities; providing a linear stage in said neural network; and training said linear stage by means of an adaptation set, wherein the step of providing said linear stage comprises the step of providing said linear stage after said intermediate stage; wherein the step of training said linear stage comprises training said linear stage so that the phoneme probability of a phoneme belonging to an absent class is equal to the phoneme probability of said phoneme calculated by said neural network before the step of providing a linear stage; and wherein the step of training said linear stage further comprises training said linear stage so that the phoneme probability of the phoneme corresponding to a voice signal sample of said adaptation set is calculated by subtracting the phoneme probabilities of all the phonemes belonging to said absent class from 1. 14. A non-transitory computer readable medium having a program recorded thereon, said computer readable medium comprising a computer program code portion for performing all the steps of claim 1 , when said computer program code portion is executed by a computer.