Speaker-independent recognition of isolated Chinese digits by a pyramidical neural net

Neural networks have been widely applied to phoneme and word recognition in a speaker-dependent mode. In this paper, a new feature extraction approach, an extended multilayered neural net model and a modified learning algorithm were applied to speaker-independent recognition of isolated Chinese digits. Experiments show that about 85 percent accuracy can be obtained.<>