Recognition of Japanese words by neural networks using vocal tract area

Abstract

The authors present a new system for Japanese word recognition by neural networks using the vocal tract area. They present a method by which the vocal tract area is directly estimated from speech waves. The estimation method applies an adaptive inverse filter to the autocorrelation coefficients. A neural network learning algorithm developed by Y. Ishida et al. (1991), which is based on the conjugate gradient method, is used. The speaker-independent word recognition results for a vocabulary of 10 Japanese words demonstrated the effectiveness of the method.<>