Evaluating the Alignment of Utterances in the Swedish Sign Language Corpus

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A8BPWBBMD" target="_blank" >RIV/00216208:11320/25:8BPWBBMD - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197547778&partnerID=40&md5=93b811fc9846df57e38ea60b0488d7b9" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197547778&partnerID=40&md5=93b811fc9846df57e38ea60b0488d7b9</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Evaluating the Alignment of Utterances in the Swedish Sign Language Corpus

Popis výsledku v původním jazyce

The Swedish Sign Language (STS) Corpus mainly contains segmentations on the lexical level (i.e. signs), which makes it difficult to extract information at clause- or utterance-like levels. In this paper, I evaluate three different methods of segmenting the data into larger units: prosodic, syntactic and translation-based utterance units. The results show that none of the utterance units have particularly high accuracy in their alignment with the others, illustrating the challenges facing researchers who are looking to extract meaningful units above the lexical level. In a second step, I extract articulation information from the corpus videos using computer vision methods, but find no clear alignment of articulatory features of the hands and head with the boundaries of the utterance units. © 2024 ELRA Language Resources Association: CC BY-NC 4.0.

Název v anglickém jazyce

Evaluating the Alignment of Utterances in the Swedish Sign Language Corpus

Popis výsledku anglicky

The Swedish Sign Language (STS) Corpus mainly contains segmentations on the lexical level (i.e. signs), which makes it difficult to extract information at clause- or utterance-like levels. In this paper, I evaluate three different methods of segmenting the data into larger units: prosodic, syntactic and translation-based utterance units. The results show that none of the utterance units have particularly high accuracy in their alignment with the others, illustrating the challenges facing researchers who are looking to extract meaningful units above the lexical level. In a second step, I extract articulation information from the corpus videos using computer vision methods, but find no clear alignment of articulatory features of the hands and head with the boundaries of the utterance units. © 2024 ELRA Language Resources Association: CC BY-NC 4.0.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Workshop Represent. Process. Sign Lang.: Eval. Sign Lang. Resour., sign-lang@LREC-COLING

ISBN

978-249381430-2

ISSN

—

e-ISSN

—

Počet stran výsledku

10

Strana od-do

36-45

Název nakladatele

Association for Computational Linguistics (ACL)

Místo vydání

—

Místo konání akce

Torino, Italia

Datum konání akce

1. 1. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—