Some preliminary results on clustering for speaker-independent word recognition
S. Levinson, Jay G. Wilpon, L. R. Rabiner, A. E. Rosenberg · The Journal of the Acoustical Society of America · 1978
Recently, Rabiner [J. Acoust. Soc. Am. 62, S64(A) (1977)] demonstrated that clustering is a powerful tool for constructing composite reference templates for speaker independent word recognition. This talk will describe a set of specially designed clustering procedures for identifying the structure in training data for a speaker independent word recognition system. The clustering procedures identify coarse structure, fine structure, overlap among clusters and outliers, and can be used interactively or automatically on either multivariate or metric data. The techniques have been applied to a large data base consisting of four repetitions of a 39-word vocabulary spoken by 50 male and 50 female speakers. Preliminary results show that the data is highly structured in a manner such that composite reference templates can be constructed in a natural way. Corroborating evidence of the structure is derived by means of a multidimensional scaling technique. Statistics of the analyses are given which support the hypothesis that the composite templates produced will form the basis for a reference set for a speaker independent word recognition system.