A DFE-based algorithm for feature selection in speech recognition
Ángel de la Torre, Antonio M. Peinado, Antonio J. Rubio, Victoria Sánchez · 2002
The algorithms for the reduction of the number of features without degrading the performance of pattern recognition systems play an important role in real applications. A new algorithm for feature selection is proposed. This algorithm is based on the discriminative feature extraction (DFE) technique and has been applied to speech recognition. The experimental results show that the recognition systems accept important reductions of the number of features without a degradation of the performance. For the representation used in our experiments, the recognition error-rate is not significantly increased when the number of components in the feature vector is reduced from 42 to 20.