On the relations between modeling approaches for information sources [speech recognition]

The authors examine the relations between maximum likelihood (ML), maximum mutual information (MMI), and minimum discrimination information (MDI) modeling approaches, which have been applied to estimating acoustic word models in speech recognition systems. The show that all three approaches can be uniformly formulated as MDI modeling approaches for estimating the acoustic models for all words simultaneously. The three approaches differ in either the probability distribution (PD) attributed to the source being modeled or in the model effectively being used. None of the approaches, however, assumes model correctness, i.e., that the source has the PD of the model. A new modeling approach is proposed, which, in contrast with the other approaches considered, directly aims at the minimization of the probability of error