@inproceedings{borstell-etal-2020-measuring,
title = "Measuring Lexical Similarity across Sign Languages in {G}lobal {S}ignbank",
author = {B{\"o}rstell, Carl and
Crasborn, Onno and
Whynot, Lori},
editor = "Efthimiou, Eleni and
Fotinea, Stavroula-Evita and
Hanke, Thomas and
Hochgesang, Julie A. and
Kristoffersen, Jette and
Mesch, Johanna",
booktitle = "Proceedings of the LREC2020 9th Workshop on the Representation and Processing of Sign Languages: Sign Language Resources in the Service of the Language Community, Technological Challenges and Application Perspectives",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/2020.signlang-1.4",
pages = "21--26",
abstract = "Lexicostatistics is the main method used in previous work measuring linguistic distances between sign languages. As a method, it disregards any possible structural/grammatical similarity, instead focusing exclusively on lexical items, but it is time consuming as it requires some comparable phonological coding (i.e. form description) as well as concept matching (i.e. meaning description) of signs across the sign languages to be compared. In this paper, we present a novel approach for measuring lexical similarity across any two sign languages using the Global Signbank platform, a lexical database of uniformly coded signs. The method involves a feature-by-feature comparison of all matched phonological features. This method can be used in two distinct ways: 1) automatically comparing the amount of lexical overlap between two sign languages (with a more detailed feature-description than previous lexicostatistical methods); 2) finding exact form-matches across languages that are either matched or mismatched in meaning (i.e. true or false friends). We show the feasability of this method by comparing three languages (datasets) in Global Signbank, and are currently expanding both the size of these three as well as the total number of datasets.",
language = "English",
ISBN = "979-10-95546-54-2",
}
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<abstract>Lexicostatistics is the main method used in previous work measuring linguistic distances between sign languages. As a method, it disregards any possible structural/grammatical similarity, instead focusing exclusively on lexical items, but it is time consuming as it requires some comparable phonological coding (i.e. form description) as well as concept matching (i.e. meaning description) of signs across the sign languages to be compared. In this paper, we present a novel approach for measuring lexical similarity across any two sign languages using the Global Signbank platform, a lexical database of uniformly coded signs. The method involves a feature-by-feature comparison of all matched phonological features. This method can be used in two distinct ways: 1) automatically comparing the amount of lexical overlap between two sign languages (with a more detailed feature-description than previous lexicostatistical methods); 2) finding exact form-matches across languages that are either matched or mismatched in meaning (i.e. true or false friends). We show the feasability of this method by comparing three languages (datasets) in Global Signbank, and are currently expanding both the size of these three as well as the total number of datasets.</abstract>
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%0 Conference Proceedings
%T Measuring Lexical Similarity across Sign Languages in Global Signbank
%A Börstell, Carl
%A Crasborn, Onno
%A Whynot, Lori
%Y Efthimiou, Eleni
%Y Fotinea, Stavroula-Evita
%Y Hanke, Thomas
%Y Hochgesang, Julie A.
%Y Kristoffersen, Jette
%Y Mesch, Johanna
%S Proceedings of the LREC2020 9th Workshop on the Representation and Processing of Sign Languages: Sign Language Resources in the Service of the Language Community, Technological Challenges and Application Perspectives
%D 2020
%8 May
%I European Language Resources Association (ELRA)
%C Marseille, France
%@ 979-10-95546-54-2
%G English
%F borstell-etal-2020-measuring
%X Lexicostatistics is the main method used in previous work measuring linguistic distances between sign languages. As a method, it disregards any possible structural/grammatical similarity, instead focusing exclusively on lexical items, but it is time consuming as it requires some comparable phonological coding (i.e. form description) as well as concept matching (i.e. meaning description) of signs across the sign languages to be compared. In this paper, we present a novel approach for measuring lexical similarity across any two sign languages using the Global Signbank platform, a lexical database of uniformly coded signs. The method involves a feature-by-feature comparison of all matched phonological features. This method can be used in two distinct ways: 1) automatically comparing the amount of lexical overlap between two sign languages (with a more detailed feature-description than previous lexicostatistical methods); 2) finding exact form-matches across languages that are either matched or mismatched in meaning (i.e. true or false friends). We show the feasability of this method by comparing three languages (datasets) in Global Signbank, and are currently expanding both the size of these three as well as the total number of datasets.
%U https://aclanthology.org/2020.signlang-1.4
%P 21-26
Markdown (Informal)
[Measuring Lexical Similarity across Sign Languages in Global Signbank](https://aclanthology.org/2020.signlang-1.4) (Börstell et al., SignLang 2020)
ACL
- Carl Börstell, Onno Crasborn, and Lori Whynot. 2020. Measuring Lexical Similarity across Sign Languages in Global Signbank. In Proceedings of the LREC2020 9th Workshop on the Representation and Processing of Sign Languages: Sign Language Resources in the Service of the Language Community, Technological Challenges and Application Perspectives, pages 21–26, Marseille, France. European Language Resources Association (ELRA).