Title :
Visualisation of long distance grammatical collocation patterns in language
Author :
Elliott, James ; Atwell, Eric ; Whyte, B.
Author_Institution :
Centre for Comput. Anal. of Language & Speech, Leeds Univ., UK
Abstract :
Research in generic unsupervised learning of language structure applied to the Search for Extra-Terrestrial Intelligence (SETI) and decipherment of unknown languages has sought to build up a generic picture of lexical and structural patterns, characteristic of natural language. As part of this toolkit, a generic system is required to facilitate the analysis of behavioural trends amongst selected pairs of terminals and non-terminals alike, regardless of which target natural language was selected. Such a tool may be useful in other areas, such as lexico-grammatical analysis or tagging of corpora. Data-oriented approaches to corpus annotation use statistical n-grams and/or constraint-based models; n-grams or constraints with wider windows can improve error rates by examining the topology of the annotation-combination space. We present a visualisation tool to help linguists find “useful” PoS-tag combinations, and cohesion between linguistic annotations at other levels, and suggest some possible applications
Keywords :
computational linguistics; data visualisation; linguistics; natural languages; statistical analysis; PoS-tag combinations; SETI; Search for Extra-Terrestrial Intelligence; annotation-combination space; behavioural trends; constraint-based models; corpora tagging; corpus annotation; data-oriented approaches; error rates; generic picture; generic system; generic unsupervised learning; language structure; lexical patterns; lexico-grammatical analysis; linguistic annotations; linguists; long distance grammatical collocation pattern visualisation; natural language; statistical n-gram; structural patterns; unknown languages; visualisation tool; Application software; Intelligent structures; Natural languages; Pattern analysis; Signal processing; Speech analysis; Tagging; Topology; Unsupervised learning; Visualization;
Conference_Titel :
Information Visualisation, 2001. Proceedings. Fifth International Conference on
Conference_Location :
London
Print_ISBN :
0-7695-1195-3
DOI :
10.1109/IV.2001.942073