Human language technology is the study of the methods by which computer programs or electronic devices can analyze, produce, modify or respond to human texts and speech. It consists of natural language processing and computational linguistics on the one hand, and speech technology on the other.
This book presents the proceedings of the 9th International Conference, Human Language Technologies – The Baltic Perspective (Baltic HLT 2020), organised in Kaunas, Lithuania on 22 and 23 September 2020. This biennial conference offers researchers a platform to share knowledge on recent advances in human language processing for the Baltic languages, as well as promoting interdisciplinary and international cooperation in human language-technology research within and beyond the Baltic States. In addition to the traditional topics of natural language processing and language technologies, this year’s conference featured a special session on resource and tool development for teaching and learning the less resourced Baltic languages. This year, 42 submissions were received, each of which was evaluated by two reviewers, resulting in a total of 34 papers being accepted for presentation and publication. The book is divided into four sections: speech and text analysis (9 papers); machine translation and natural understanding (6 papers); tools and resources (14 papers); and language learning resources (5 papers).
Providing a fascinating overview of current research in the field from a primarily Baltic perspective, the book will be of interest to all those whose work involves human language technology.
págs. 3-10
págs. 11-18
págs. 19-26
Similarities and Differences of Lithuanian Functional Styles: A Quantitative Perspective
págs. 27-31
Targeted Aspect-Based Sentiment Analysis for Lithuanian Social Media Reviews
Mažvydas Petkevičius, Daiva Vitkutė-Adžgauskienė, Darius Amilevičius
págs. 32-38
págs. 39-46
págs. 47-54
págs. 55-61
págs. 62-69
págs. 73-79
Robust Neural Machine Translation: Modeling Orthographic and Interpunctual Variation
págs. 80-86
págs. 87-94
págs. 95-102
págs. 103-110
LVBERT: Transformer-Based Model for Latvian Language Understanding
págs. 111-115
págs. 119-122
págs. 123-126
págs. 127-134
págs. 135-141
págs. 142-149
págs. 150-157
págs. 158-165
Berri Corpus Manager: A Corpus Analysis Tool Using MongoDB Technology
págs. 166-173
págs. 174-181
Language Technology Platform for Public Administration
Raivis Skadins, Marcis Pinnis, Artūrs Vasiļevskis, Andrejs Vasiljevs, Valters Šics, Roberts Rozis, Andis Lagzdins
págs. 182-190
págs. 191-198
págs. 199-206
págs. 207-214
Development and Research in Lithuanian Language Technologies (2016–2020)
Andrius Utka, Jurgita Vaičenonienė, Monika Briedienė, Tomas Krilavičius
págs. 215-222
págs. 225-232
Lithuanian Pedagogic Corpus: Correlations Between Linguistic Features and Text Complexity
págs. 233-240
Detailed Error Annotation for Morphologically Rich Languages: Latvian Use Case
Roberts Dargis, Ilze Auzina, Kristine Levane-Petrova, Inga Kaija
págs. 241-244
The First Corpus-Driven Lexical Database of Lithuanian as L2
Jolanta Kovalevskaitė, Loïc Boizou, Agnė Bielinskienė, Laima Jancaitė, Erika Rimkutė
págs. 245-252
Error Tagging in the Lithuanian Learner Corpus
Jūratė Ruzaitė, Sigita Dereškevičiūtė, Viktorija Kavaliauskaitė Vilkinienė, Eglė Krivickaitė Leišienė
págs. 253-260
© 2001-2024 Fundación Dialnet · Todos los derechos reservados