A Structured Language Model
Ciprian Chelba
- 07 Jul 1997
- pp 498-500
TL;DR: A language model is presented that develops syntatic structure and uses it to extract meaningful information from the word history, thus enabling the use of long distance dependencies and its probabilistic parametrization.
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Abstract: The paper presents a language model that develops syntatic structure and uses it to extract meaningful information from the word history, thus enabling the use of long distance dependencies The model assigns probability to every joint sequence of words-binary-parse-structure with headword annotation The model, its probabilistic parametrization, and a set of experiments meant to evaluate its predictive power are presented
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Citations
Structured language modeling
Ciprian Chelba,Frederick Jelinek +1 more
TL;DR: An attempt at using the syntactic structure in natural language for improved language models for speech recognition using an original probabilistic parameterization of a shift-reduce parser.
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TL;DR: In this article, a speech input mode dynamically reports partial semantic parses, while audio captioning is still in progress, which is a significant departure from the turn-taking nature of a spoken dialogue.
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Francisco M. Galanes,Hsiao-Wuen Hon,James D. Jacoby,Renaud J. Lecoueche,Stephen F. Potter +4 more
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TL;DR: In this article, a web server is used to generate client side markups that include recognition and/or audible prompting, such as a question, answer, confirmation, command or statement.
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