Isolated-Word Recognition with Penalized Logistic Regression Machines

We propose a new approach to isolated-word speech recognition based on penalized logistic regression machines (PLRMs). With this approach we combine the hidden Markov model (HMM) with multiclass logistic regression resulting in a powerful speech recognizer which provides us with the posterior probability for each word. Experiments on the English E-set show significant improvements compared to conventional HMM-based speech recognition