This paper proposes a method for smoothing the Hidden Markov Models (HMM) with the VQ done by means of the Self Organising Feature Maps (SOFM). The use SOFM gives rise to a special property of the probability of emission matrix of the HMM. This property is that when ordering the probability of emission matrix following the order of the SOFM; neighbouring symbols will have similar probabilities. In order to smooth the HMM we propose to filter the probability of emission matrix by a filter that makes use of this property. We also compare this method with another method for smoothing the HMM; the coocurrence method. The recognition rate improvement achieved by the method that we propose is better than the recognition rate obtained by means of the coocurrence method.