Abstract: Describes a sentence understanding system that is completely based on learned methods both for understanding individual sentences and for ...

We describe the models used for each of three stages in the understanding: seman- tic parsing, semantic classification, and discourse modeling. When we ran this ...

Describes a sentence understanding system that is completely based on learned methods both for understanding individual sentences and for determining their ...

Nov 28, 2023 · Hidden Markov Models (HMMs) are a type of probability model that can be used in Natural Language Understanding (NLU).

Hidden understanding models are an innovative class of statistical mechanisms that, given a string of words, determines the most likely meaning for the string.

Dec 30, 2023 · HMMs can capture the underlying probabilistic relationships between observed words and their corresponding PoS tags. A Hidden Markov Model (HMM) ...

We describe and evaluate hidden understanding models, a statistical learning approach to natural language understanding. Given a string of words, ...

It is the purpose of this tutorial paper to give an introduction to the theory of Markov models, and to illustrate how they have been applied to problems in ...

Oct 15, 2023 · This article aims to demystify the underlying mechanisms of Large Language Models, focusing on the concept of word-to-vector calculations and embeddings.

Richard M. Schwartz, Scott Miller, David Stallard, John Makhoul: Language understanding using hidden understanding models. ICSLP 1996: 997-1000.