Constrained line search optimization for discriminative training of HMMS

摘要

An exemplary method for optimizing a continuous density hidden Markov model (CDHMM) includes imposing a constraint for discriminative training, approximating an objective function as a smooth function of CDHMM parameters and performing a constrained line search on the smoothed function to optimize values of the CDHMM parameters. Various other methods, devices and systems are disclosed.