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Raciolinguistics

Edited by H. Samy Alim, John R. Rickford, and Arnetha F. Ball

Raciolinguistics "Brings together a critical mass of scholars to form a new field dedicated to theorizing and analyzing language and race together."


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Sociolinguistics from the Periphery

By Sari Pietikäinen, FinlandAlexandra Jaffe, Long BeachHelen Kelly-Holmes, and Nikolas Coupland

Sociolinguistics from the Periphery "presents a fascinating book about change: shifting political, economic and cultural conditions; ephemeral, sometimes even seasonal, multilingualism; and altered imaginaries for minority and indigenous languages and their users."


Academic Paper


Title: Dependency-based n-gram models for general purpose sentence realisation
Author: Yuqing Guo
Institution: Toshiba (China) Research and Development Center
Author: Haifeng Wang
Institution: Baidu
Author: Josef Van Genabith
Email: click here TO access email
Institution: Dublin City University
Linguistic Field: Computational Linguistics; Semantics; Syntax
Subject Language: Chinese, Mandarin
English
Abstract: This paper presents a general-purpose, wide-coverage, probabilistic sentence generator based on dependency n-gram models. This is particularly interesting as many semantic or abstract syntactic input specifications for sentence realisation can be represented as labelled bi-lexical dependencies or typed predicate-argument structures. Our generation method captures the mapping between semantic representations and surface forms by linearising a set of dependencies directly, rather than via the application of grammar rules as in more traditional chart-style or unification-based generators. In contrast to conventional n-gram language models over surface word forms, we exploit structural information and various linguistic features inherent in the dependency representations to constrain the generation space and improve the generation quality. A series of experiments shows that dependency-based n-gram models generalise well to different languages (English and Chinese) and representations (LFG and CoNLL). Compared with state-of-the-art generation systems, our general-purpose sentence realiser is highly competitive with the added advantages of being simple, fast, robust and accurate.

CUP AT LINGUIST

This article appears IN Natural Language Engineering Vol. 17, Issue 4.

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