Automatic detection of prolonged fricative phonemes with the Hidden Markov Models approach

The Hidden Markov Model (HMM) is a stochastic approach to recognition of patterns appearing in an input signal. In the work author's implementation of the HMM were used to recognize speech disorders - prolonged fricative phonemes. To achieve the best recognition effectiveness and simultaneously preserve reasonable time required for calculations two problems need to be addressed: the choice of the HMM and the proper preparation of an input data. Tests results for recognition of the considered type of speech disorders are presented for HMM models with different number of states and for different sizes of codebooks.