@inproceedings{mostowski:26053:sign-lang:lrec,
  author    = {Mostowski, Piotr and Kuder, Anna and W{\'o}jcicka, Joanna},
  title     = {Assisting Corpus Annotation: Automatic {BIO}-Tagging of Clause-Like Units in {Polish} {Sign} {Language}. A Pilot Study on Corpus Data},
  pages     = {351--360},
  editor    = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Mesch, Johanna and Schulder, Marc},
  booktitle = {Proceedings of the {LREC2026} 12th Workshop on the Representation and Processing of Sign Languages: Language in Motion},
  maintitle = {15th International Conference on Language Resources and Evaluation ({LREC} 2026)},
  publisher = {{ELRA Language Resources Association (ELRA)}},
  address   = {Palma, Mallorca, Spain},
  day       = {16},
  month     = may,
  year      = {2026},
  isbn      = {978-2-493814-82-1},
  language  = {english},
  url       = {https://www.sign-lang.uni-hamburg.de/lrec/pub/26053.html},
  abstract  = {The creation of large-scale sign language corpora is often bottlenecked by the labour-intensive process of multi-layered annotation that requires manual analysis. One of the annotation steps is the challenging and time-consuming task of segmenting continuous signing into clause-like-units (CLUs). In this paper, we propose an automated segmentation framework for Polish Sign Language (PJM) designed to support manual annotation. To detect sentence boundaries, we adapt the Multi-Stage Temporal Convolutional Network (MS-TCN) architecture, enhanced with a Channel Attention mechanism, to effectively fuse multimodal skeleton features (hands, body, and face) extracted via MediaPipe. We evaluate the model on a diverse subset of the PJM Corpus (40 video files, 25 signers), containing nearly 16,000 manually annotated clauses prior to the start of this study. The proposed method achieves a Segmental F1-score of 75.43{\%} at IoU = 0.10 and 57.52{\%} at IoU = 0.50, demonstrating a strong capability in localising sentence boundaries. Furthermore, ablation studies reveal that fusing manual kinematics with non-manual prosodic cues (face) yields a significant performance gain (+13.6 pp) over unimodal baselines, empirically confirming the linguistic necessity of incorporating both manual and non-manual articulators in the process of sentence delimitation. The solution offers a viable means for reducing CLU annotation time by automatically generating high-quality clause boundary proposals.}
}

@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{mostowski:18045:sign-lang:lrec,
  author    = {Mostowski, Piotr and Kuder, Anna and Filipczak, Joanna and Rutkowski, Pawe{\l}},
  title     = {Workflow Management and Quality Control in the Development of the {PJM} Corpus: The Use of an Issue-Tracking System},
  pages     = {133--138},
  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/18045.html},
  abstract  = {The main goal of the present paper is to describe a workflow management and quality assurance system used in the project of developing the Polish Sign Language (polski j{\k e}zyk migowy, PJM) Corpus currently underway at the University of Warsaw, Poland. To ensure a satisfactory level of annotation quality, we implemented an external issue tracking system as a basic tool to manage all stages of the annotation process: segmenting the video recording into individual signs, adding glosses to the delineated signs, segmenting text into clauses, translating text into written Polish and adding grammar tags marking different language phenomena. This paper offers a detailed overview of the procedures that we employ, illustrating the most important advantages and disadvantages of our approach and the choices we have made.}
}