A Language Model Sensitive to Discourse Context
- The paper proposes a meta language model that can dynamically incorporate the influence of wider discourse context. The model provides a conditional probability in forms of P (text|context), where the context can be arbitrary length of text, and is used to influence the probability distribution over documents. A preliminary evaluation using a 3-gram model as the base language model shows significant reductions in perplexity by incorporating discourse context.
Author: | Tae-Gil Noh, Sebastian Padó |
---|---|
URN: | https://nbn-resolving.org/urn:nbn:de:gbv:hil2-opus-2822 |
Parent Title (English): | Proceedings of the 12th edition of the KONVENS conference |
Document Type: | Conference Proceeding |
Language: | English |
Date of Publication (online): | 2014/10/23 |
Release Date: | 2014/10/23 |
Tag: | Statistische Methoden Machine Learning; Statistical Methods |
GND Keyword: | Maschinelles Lernen |
First Page: | 201 |
Last Page: | 206 |
PPN: | Link zum Katalog |
Institutes: | Fachbereich III / Informationswissenschaft und Sprachtechnologie |
DDC classes: | 400 Sprache / 400 Sprache, Linguistik |
Collections: | KONVENS 2014 / Proceedings of the 12th KONVENS 2014 |
Licence (German): | ![]() |