@inproceedings{schulder:24034:sign-lang:lrec, author = {Schulder, Marc and Bigeard, Sam and Kopf, Maria and Hanke, Thomas and Kuder, Anna and W{\'o}jcicka, Joanna and Mesch, Johanna and Bj{\"o}rkstrand, Thomas and Vacalopoulou, Anna and Vasilaki, Kyriaki and Goulas, Theodoros and Fotinea, Stavroula-Evita and Efthimiou, Eleni}, title = {Signs and Synonymity: Continuing Development of the {Multilingual} {Sign} {Language} {Wordnet}}, pages = {343--353}, editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Mesch, Johanna and Schulder, Marc}, booktitle = {Proceedings of the {LREC-COLING} 2024 11th Workshop on the Representation and Processing of Sign Languages: Evaluation of Sign Language Resources}, maintitle = {2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation ({LREC-COLING} 2024)}, publisher = {{ELRA Language Resources Association (ELRA) and the International Committee on Computational Linguistics (ICCL)}}, address = {Torino, Italy}, day = {25}, month = may, year = {2024}, isbn = {978-2-493814-30-2}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/24034.html}, abstract = {The Multilingual Sign Language Wordnet is the first publicly available wordnet resource for sign languages. It is a growing multilingual resource providing data for eight sign languages to date. During the initial phase of its creation, the focus lay on producing the infrastructure to support various languages and to produce initial sets of content for them. This article represents the start of the second phase, in which the focus is moved to establishing overlapping coverage across the different sign languages. Building on the data produced so far, a new feature to assist annotation is introduced which leverages established partial synonymy between signs (inter- and cross-lingually) to discover likely additional synonymies. Other improvements to the annotation interface and workflow build directly on the experiences from the first phase. Working with the updated annotation interface, new data is produced for Polish Sign Language, Greek Sign Language and Swedish Sign Language.} } @inproceedings{kuder:22020:sign-lang:lrec, author = {Kuder, Anna}, title = {Making Sign Language Corpora Comparable: A Study of Palm-Up and Throw-Away in {Polish} {Sign} {Language}, {German} {Sign} {Language}, and {Russian} {Sign} {Language}}, pages = {110--117}, editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna and Schulder, Marc}, booktitle = {Proceedings of the {LREC2022} 10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources}, maintitle = {13th International Conference on Language Resources and Evaluation ({LREC} 2022)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Marseille, France}, day = {25}, month = jun, year = {2022}, isbn = {979-10-95546-86-3}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/22020.html}, abstract = {This paper is primarily devoted to describing the preparation phase of a large-scale comparative study based on naturalistic linguistic data drawn from multiple sign language corpora. To provide an example, I am using my current project on manual gestural elements in Polish Sign Language, German Sign Language, and Russian Sign Language. The paper starts with a description of the reasons behind undertaking this project. Then, I describe the scope of my study, which is focused on two manual elements present in all three mentioned sign languages: palm-up and throw-away; and the three corpora which are my data sources. This is followed by a presentation of the steps taken in the initial stages of the project in order to make the data comparable. Those steps are: choosing the adequate data samples from all three corpora, gathering all data within the chosen software, and creating an annotation schema that builds on the annotations already present in all three corpora. Even though the project is still underway, and the annotation process is ongoing, preliminary discussions about the nature of the analysed manual activities are presented based on the initial annotations for the sake of evaluating the created annotation schema. I conclude the paper with some remarks about the performance of the employed methodology.} } @inproceedings{kuder:22010:sign-lang:lrec, author = {Kuder, Anna and W{\'o}jcicka, Joanna and Mostowski, Piotr and Rutkowski, Pawe{\l}}, title = {Open Repository of the {Polish} {Sign} {Language} {Corpus}: Publication Project of the {Polish} {Sign} {Language} {Corpus}}, pages = {118--123}, editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna and Schulder, Marc}, booktitle = {Proceedings of the {LREC2022} 10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources}, maintitle = {13th International Conference on Language Resources and Evaluation ({LREC} 2022)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Marseille, France}, day = {25}, month = jun, year = {2022}, isbn = {979-10-95546-86-3}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/22010.html}, abstract = {Between 2010 and 2020, the research team of the Section for Sign Linguistics collected, annotated, and translated a large corpus of Polish Sign Language (polski j{\k e}zyk migowy, PJM). After this task was finished, a substantial part of the gathered materials was published online as the Open Repository of the Polish Sign Language Corpus. The current paper gives an overview of the process of converting the material from the Corpus into the Repository. If presents and explains the decisions made along the way and describes the process of data preparation and publication. There are two levels of access to the Repository, which are meant to fulfil the needs of a wide range of public users, from members of the Deaf community, through hearing students of PJM, sign language teachers and interpreters, to users with academic background. We describe how corpus material available in open access was prepared to be searchable by text type and elicitation tasks, by sociolinguistic metadata, and by translation into written Polish. We go on to explain how access for research purposes differs from open access. We present possible ways in which data gathered in the Repository may be used by members of the signing community in Poland and abroad.} } @inproceedings{kuder:18033:sign-lang:lrec, author = {Kuder, Anna and Filipczak, Joanna and Mostowski, Piotr and Rutkowski, Pawe{\l} and Johnston, Trevor}, title = {What Corpus-based Research on Negation in {Auslan} and {PJM} Tells Us about Building and Using Sign Language Corpora}, pages = {101--106}, editor = {Bono, Mayumi and Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna and Osugi, Yutaka}, booktitle = {Proceedings of the {LREC2018} 8th Workshop on the Representation and Processing of Sign Languages: Involving the Language Community}, maintitle = {11th International Conference on Language Resources and Evaluation ({LREC} 2018)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Miyazaki, Japan}, day = {12}, month = may, year = {2018}, isbn = {979-10-95546-01-6}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/18033.html}, abstract = {In this paper, we would like to discuss our current work on negation in Auslan (Australian Sign Language) and PJM (Polish Sign Language, polski j{\k e}zyk migowy) as an example of experience in using sign language corpus data for research purposes. We describe how we prepared the data for two detailed empirical studies, given similarities and differences between the Australian and Polish corpus projects. We present our findings on negation in both languages, which turn out to be surprisingly similar. At the same time, what the two corpus studies show seems to be quite different from many previous descriptions of sign language negation found in the literature. Some remarks on how to effectively plan and carry out the annotation process of sign language texts are outlined at the end of the present paper, as they might be helpful to other researchers working on designing a corpus. Our work leads to two main conclusions: (1) in many cases, usage data may not be easily reconciled with intuitions and assumptions about how sign languages function and what their grammatical characteristics are like, (2) in order to obtain representative and reliable data from large-scale corpora one needs to plan and carry out the annotation process very thoroughly.} } @inproceedings{kimmelman-etal-2018-ipsl:lrec, author = {Kimmelman, Vadim and Klezovich, Anna and Moroz, George}, title = {{IPSL}: A Database of Iconicity Patterns in Sign Languages. Creation and Use}, pages = {4230--4234}, editor = {Calzolari, Nicoletta and Choukri, Khalid and Cieri, Christopher and Declerck, Thierry and Goggi, Sara and Hasida, Koiti and Isahara, Hitoshi and Maegaard, Bente and Mariani, Joseph and Mazo, H{\'e}l{\`e}ne and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios and Tokunaga, Takenobu}, booktitle = {11th International Conference on Language Resources and Evaluation ({LREC} 2018)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Miyazaki, Japan}, day = {7--12}, month = may, year = {2018}, isbn = {979-10-95546-00-9}, language = {english}, url = {https://aclanthology.org/L18-1667}, abstract = {We created the first large-scale database of signs annotated according to various parameters of iconicity. The signs represent concrete concepts in seven semantic fields in nineteen sign languages; 1542 signs in total. Each sign was annotated with respect to the type of form-image association, the presence of iconic location and movement, personification, and with respect to whether the sign depicts a salient part of the concept. We also created a website: https://sl-iconicity.shinyapps.io/iconicity patterns/ with several visualization tools to represent the data from the database. It is possible to visualize iconic properties of separate concepts or iconic properties of semantic fields on the map of the world, and to build graphs representing iconic patterns for selected semantic fields. A preliminary analysis of the data shows that iconicity patterns vary across semantic fields and across languages. The database and the website can be used to further study a variety of theoretical questions related to iconicity in sign languages.} } @inproceedings{yu-etal-2018-sign:lrec, author = {Yu, Shi and Geraci, Carlo and Abner, Natasha}, title = {Sign Languages and the Online World Online Dictionaries {\&} Lexicostatistics}, pages = {4235--4240}, editor = {Calzolari, Nicoletta and Choukri, Khalid and Cieri, Christopher and Declerck, Thierry and Goggi, Sara and Hasida, Koiti and Isahara, Hitoshi and Maegaard, Bente and Mariani, Joseph and Mazo, H{\'e}l{\`e}ne and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios and Tokunaga, Takenobu}, booktitle = {11th International Conference on Language Resources and Evaluation ({LREC} 2018)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Miyazaki, Japan}, day = {7--12}, month = may, year = {2018}, isbn = {979-10-95546-00-9}, language = {english}, url = {https://aclanthology.org/L18-1668}, abstract = {Several online dictionaries documenting the lexicon of a variety of sign languages (SLs) are now available. These are rich resources for comparative studies, but there are methodological issues that must be addressed regarding how these resources are used for research purposes. We created a web-based tool for annotating the articulatory features of signs (handshape, location, movement and orientation). Videos from online dictionaries may be embedded in the tool, providing a mechanism for large-scale theoretically-informed sign language annotation. Annotations are saved in a spreadsheet format ready for quantitative and qualitative analyses. Here, we provide proof of concept for the utility of this tool in linguistic analysis. We used the SL adaptation of the Swadesh list (Woodward, 2000) and applied lexicostatistic and phylogenetic methods to a sample of 23 SLs coded using the web-based tool; supplementary historic information was gathered from the Ethnologue of World Languages and other online sources. We report results from the comparison of all articulatory features for four Asian SLs (Chinese, Hong Kong, Taiwanese and Japanese SLs) and from the comparison of handshapes on the entire 23 language sample. Handshape analysis of the entire sample clusters all Asian SLs together, separated from the European, American, and Brazilian SLs in the sample, as historically expected. Within the Asian SL cluster, analyses also show, for example, marginal relatedness between Chinese and Hong Kong SLs.} }