Specific distance for feature selection in speech recognition
Document typeConference report
Rights accessOpen Access
In this paper, the use of a specific metric as a feature selection step is investigated. The feature selection step tries to model the correlation among adjacent feature vectors and the variability of the speech. We propose a new procedure which performs the feature selection in two steps. The first step takes into account the temporal correlation among the N feature vectors of a template in order to obtain a new set of feature vectors which are uncorrelated. This step gives a new template of M feature vectors, with M « N. The second step defines a specific distance among feature vectors to take into account the frequency discrimination features which discriminate each word of the vocabulary from the others or a set of them. Thus, the new feature vectors are uncorrelated in time and discriminant in frequency.
CitationLleida, E., Nadeu, C., Mariño, J.B., Monte, E., Moreno, A. Specific distance for feature selection in speech recognition. A: NATO ASI: Advanced Study Institute. "NATO ASI: Speech recognition and understanding: recent advances, trends and applications". Springer, 1990, p. 513-518.