Enhanced control and estimation of parameters for a telephone based isolated digit recognizer

The paper studies the use of discriminative techniques for a telephone based isolated digit recognizer with respect to a reduced system complexity. The combination of linear discriminant analysis (LDA) and minimum error classification (MEC) training provides improved system performance at reduced costs for the training process and for the application. Experiments are performed on an isolated digit database recorded over public lines including approximately 700 speakers. The use of a single linear transformation matrix based on LDA allows the use of density modeling, that doesn't consider variances explicitly at a high recognition rate. Minimum classification error training is found to perform best in case of a small amount of system parameters. A reduction of error rate up to 80% was achieved by the combination of the two methods for such a system configuration.