Title :
Word recognition with the feature finding neural network (FFNN)
Author_Institution :
Drittes Phys. Inst., Gottingen Univ., Germany
fDate :
30 Sep-1 Oct 1991
Abstract :
An overview of the architecture and capabilities of the work recognizer FFNN (`feature finding neural network´) is given. FFNN finds features in a self-organizing way which are relatively invariant in the presence of time distortions and changes in speaker characteristics. Fast and optimal feature selection rules have been developed to perform this task. With FFNN, essential problems of word recognition can be solved, among them a special case of the figure ground problem. FFNN is faster than the classical DTW and HMM recognizers and yields similar recognition rates
Keywords :
neural nets; speech recognition; architecture; feature finding neural network; feature selection rules; image processing; word recognition; Biological neural networks; Brain modeling; Electronic mail; Hidden Markov models; Neural networks; Nonlinear distortion; Pattern recognition; Predictive models; Testing; Vocabulary;
Conference_Titel :
Neural Networks for Signal Processing [1991]., Proceedings of the 1991 IEEE Workshop
Conference_Location :
Princeton, NJ
Print_ISBN :
0-7803-0118-8
DOI :
10.1109/NNSP.1991.239513
