Publishing Partner: Cambridge University Press CUP Extra Wiley-Blackwell Publisher Login
amazon logo
More Info


New from Oxford University Press!

ad

The Social Origins of Language

By Daniel Dor

Presents a new theoretical framework for the origins of human language and sets key issues in language evolution in their wider context within biological and cultural evolution


New from Cambridge University Press!

ad

Preposition Placement in English: A Usage-Based Approach

By Thomas Hoffmann

This is the first study that empirically investigates preposition placement across all clause types. The study compares first-language (British English) and second-language (Kenyan English) data and will therefore appeal to readers interested in world Englishes. Over 100 authentic corpus examples are discussed in the text, which will appeal to those who want to see 'real data'


New from Brill!

ad

Free Access 4 You

Free access to several Brill linguistics journals, such as Journal of Jewish Languages, Language Dynamics and Change, and Brill’s Annual of Afroasiatic Languages and Linguistics.


Academic Paper


Title: Probabilistic and Possibilistic Language Models Based on the World Wide Web
Paper URL: http://www.isca-speech.org/archive/interspeech_2009/i09_2699.html
Author: Stanislas Oger
Institution: University of Avignon
Author: Georges Linarès
Institution: University of Avignon
Linguistic Field: Computational Linguistics; Text/Corpus Linguistics
Abstract: Usually, language models are built either from a closed corpus, or by using World Wide Web retrieved documents, which are considered as a closed corpus themselves. In this paper we propose several other ways, more adapted to the nature of the Web, of using this resource for language modeling. We first start by improving an approach consisting in estimating n-gram probabilities from Web search engine statistics. Then, we propose a new way of considering the information extracted from the Web in a probabilistic framework. Then, we also propose to rely on Possibility Theory for effectively using this kind of information. We compare these two approaches on two automatic speech recognition tasks: (i) transcribing broadcast news data, and (ii) transcribing domain-specific data, concerning surgical operation film comments. We show that the two approaches are effective in different situations.
Type: Individual Paper
Status: Completed
Venue: International Speech Communication Association (ISCA)
Publication Info: Proceedings of the 10th Annual Conference of the International Speech Communication Association (InterSpeech)
URL: http://www.isca-speech.org/archive/interspeech_2009/i09_2699.html


Back
Add a new paper
Return to Academic Papers main page
Return to Directory of Linguists main page