Markov models are extremely useful as a general, widely applicable tool for many areas in
statistical pattern recognition. This unique text/reference places the formalism of Markov …

This paper compares various category-based language models when used in conjunction
with a word-based trigram by means of linear interpolation. Categories corresponding to …

Page 1 Gernot A. Fink Mustererkennung mit Markov-Modellen Theorie - Praxis -
Anwendungsgebiete EB Teubner Page 2 Leitfäden der Informatik Gernot A. Fink …

Standard statistical language modeling techniques suffer from sparse data problems when
applied to real tasks in speech recognition, where large amounts of domain-dependent text …

A novel approach is presented to class-based language modeling based on part-of-speech
statistics. It uses a deterministic word-to-class mapping, which handles words with …

This paper compares various class-based language models when used in conjunction with
a word-based trigram language model by means of linear interpolation. For class-based …

This paper is devoted to the estimation of stochastic context-free grammars (SCFGs) and
their use as language models. Classical estimation algorithms, together with new ones that …

Language models are computational techniques and structures that describe word
sequences produced by human subjects, and the work presented here considers primarily …

Natural languages are known for their expressive richness. Many sentences can be used to
represent the same underlying meaning. Only modelling the observed surface word …

The main goal of the present work is to explore the use of rich lexical information in
language modelling. We reformulated the task of a language model from predicting the next …