9. A system as claimed in claim 1 wherein the GMM based HMM provides the observation probabilities for a higher level HMM.
1. A signal processing system for processing a plurality of multi-element data encoding vectors, the system: having means for deriving the data encoding vectors from input signals; being arranged to process the data encoding vectors using a Gaussian Mixture Model (GMM) based Hidden Markov Model (HMM), the GMM based HMM having at least one class mean vector having multiple elements; being arranged to process the elements of the class mean vector(s) by an iterative optimisation procedure; characterised in that the system is also arranged to scale the elements of the class mean vector(s) during the optimisation procedure to provide for the class mean vector(s) to have constant modulus at each iteration, and to normalise the data encoding vectors input to the GMM based HMM.