Lattice-Based Discriminative Training: Theory and Practice

Опубликовано 7 сентября 2016, 16:42

Lattice-based discriminative training techniques such as MMI and MPE have been increasingly widely used in recent years.  I will review these model based discriminative training technique and also the newer feature-based techniques such as fMPE.  I will discuss some of the practical issues that are relevant to discriminative training, such as lattice generation, lattice depth and quality, probability scaling, I-smoothing, language models, alignment consistency, and various other issues for feature-based discriminative training, and will discuss more recent improvements such as frame-weighted MPE (MPFE), and give an overview of some recent unrelated work that I have been doing.