Phoneme recognition using time-dependent versions of self-organizing maps

Two modifications of the self-organizing map (SOM) are proposed that, unlike the original algorithm, take into account time-dependent features of the input signal. In the first, a time average of a sequence of responses of one SOM is found, and this is recognized by another SOM. In the second, successive input patterns are concatenated together and recognized by the SOM. Comparing the results to those of a recognition system utilizing the original SOM, it was found that one could improve the recognition of isolated phonemes from 10.4% of errors to 7.0% and 5.0% of errors for the integration model and concatenation model, respectively. The improvement in a full-scale system where phoneme segments are also to be located is from 9.2% of errors to 8.2% and 7.6% of errors for the new methods, respectively