Isolated word recognition using a hybrid neural network
V. Tabarabaee, B. Azimisadjadi, Seyed Bahram ZahirAzami, Carrie L. Lucas · 2002
A hybrid neural network is described. It consists of a Kohonen map and a perceptron. The hybrid is proposed firstly for speaker independent, isolated word recognition. However, it may also be used for other classification problems. The novel idea in this system is the usage of a Kohonen map as the feature extractor which converts phonetic similarities of the speech frames into spatial adjacency in the map. This property simplifies the classification task. The system performance was evaluated for recognition of a limited number of Farsi words (numbers "zero" through "ten"). The overall performance of the recognizer showed to be 93.82%.>