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25th Annual Conference of the European Association for Machine Translation, EAMT 2024

作者： Roussis, Dimitris Sofianopoulos, Sokratis Piperidis, Stelios Institute for Speech and Language Processing Athena RC Artemidos 6 & Epidavrou Athens Greece

ISBN: (纸本)9781068690709

The increasing volume of scientific research necessitates effective communication across language barriers. Machine translation (MT) offers a promising solution for accessing international publications. However, the scientific domain presents unique challenges due to its specialized vocabulary and complex sentence structures. In this paper, we present the development of a collection of parallel and monolingual corpora for the scientific domain. The corpora target the language pairs Spanish-English, French-English, and Portuguese-English. For each language pair, we create a large general scientific corpus as well as four smaller corpora focused on the domains of: Cancer Research, Energy Research, Neuroscience, and Transportation research. To evaluate the quality of these corpora, we utilize them for fine-tuning general-purpose neural machine translation (NMT) systems. We provide details regarding the corpus creation process, the fine-tuning strategies employed, and we conclude with the evaluation results. © 2024 The authors, © 2024 European Association for Machine Translation.

关键词： Neural machine translation

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Methodological issues regarding the semi-automatic UD treebank creation of under-resourced languages: the case of Pomak 6

Methodological issues regarding the semi-automatic UD treeba...

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6th Workshop on Universal Dependencies (UDW, GURT/SyntaxFest 2023), UDW 2023

作者： Markantonatou, Stella Constantinides, Nicolaos Th. Stamou, Vivian Arampatzakis, Vasileios Krimpas, Panagiotis G. Pavlidis, George Institute for Language and Speech Processing Athena R.C. Greece

ISBN: (纸本)9781959429340

Pomak is an endangered oral Slavic language of Thrace/Greece. We present a short description of its interesting morphological and syntactic features in the UD framework. Because the morphological annotation of the treebank takes advantage of existing resources, it requires a different methodological approach from the one adopted for syntactic annotation that has started from scratch. It also requires the option of obtaining morphological predictions/evaluation separately from the syntactic ones with state-of-the-art NLP tools. Active annotation is applied in various settings in order to identify the best model that would facilitate the ongoing syntactic annotation. © 2023 Association for Computational Linguistics

关键词： Syntactics

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ASR pipeline for low-resourced languages: A case study on Pomak 2

ASR pipeline for low-resourced languages: A case study on Po...

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2nd Workshop on NLP Applications to Field Linguistics, FieldMatters 2023

作者： Tsoukala, Chara Kritsis, Kosmas Douros, Ioannis Katsamanis, Athanasios Kokkas, Nikolaos Arampatzakis, Vasileios Sevetlidis, Vasileios Markantonatou, Stella Pavlidis, George Institute for Language and Speech Processing Athena R.C. Greece

ISBN: (纸本)9781959429609

Automatic speech Recognition (ASR) models can aid field linguists by facilitating the creation of text corpora from oral material. Training ASR systems for low-resource languages can be a challenging task not only due to lack of resources but also due to the work required for the preparation of a training dataset. We present a pipeline for data processing and ASR model training for low-resourced languages, based on the language family. As a case study, we collected recordings of Pomak, an endangered South East Slavic language variety spoken in Greece. Using the proposed pipeline, we trained the first Pomak ASR model. © 2023 Association for Computational Linguistics.

关键词： Pipelines

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LAR-ECHR: A New Legal Argument Reasoning Task and Dataset for Cases of the European Court of Human Rights 6

LAR-ECHR: A New Legal Argument Reasoning Task and Dataset fo...

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6th Natural Legal language processing Workshop 2024, NLLP 2024, co-located with the 2024 Conference on Empirical Methods in Natural language processing

作者： Chlapanis, Odysseas S. Galanis, Dimitrios Androutsopoulos, Ion Department of Informatics Athens University of Economics and Business Greece Institute for Language and Speech Processing Athena Research Center Greece Archimedes Unit Athena Research Center Greece

ISBN: (纸本)9798891761834

We present Legal Argument Reasoning (LAR), a novel task designed to evaluate the legal reasoning capabilities of Large language Models (LLMs). The task requires selecting the correct next statement (from multiple choice options) in a chain of legal arguments from court proceedings, given the facts of the case. We constructed a dataset (LAR-ECHR) for this task using cases from the European Court of Human Rights (ECHR). We evaluated seven general-purpose LLMs on LAR-ECHR and found that (a) the ranking of the models is aligned with that of LegalBench, an established US-based legal reasoning benchmark, even though LAR-ECHR is based on EU law, (b) LAR-ECHR distinguishes top models more clearly, compared to LegalBench, (c) even the best model (GPT-4o) obtains 75.8% accuracy on LAR-ECHR, indicating significant potential for further model improvement. The process followed to construct LAR-ECHR can be replicated with cases from other legal systems. ©2024 Association for Computational Linguistics.

关键词： Case based reasoning

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Multilingual Synthesis of Depictions through Structured Descriptions of Sign: An Initial Case Study 11

Multilingual Synthesis of Depictions through Structured Desc...

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11th Workshop on the Representation and processing of Sign languages: Evaluation of Sign language Resources, sign-lang@LREC-COLING 2024

作者： McDonald, John Efthimiou, Eleni Fotinea, Stavroula-Evita Wolfe, Rosalee School of Computing DePaul University ChicagoIL United States Institute for Language and Speech Processing ATHENA Research Center Athens Greece

ISBN: (纸本)9782493814302

Sign language synthesis systems must contend with an enormous variety of possible target languages across the world, and in many locations, such as Europe, the number of sign languages that can be found in a relatively limited geographical area can be surprising. For such a synthesis system to be widely useful, it must not be limited to only one target language. This presents challenges both for the linguistic models and the animation systems that drive these displays. This paper presents a case study for animating discourse in three target languages, French, Greek and German, generated directly from the same base linguistic description. The case study exploits non-lexical constructs in sign, which are more common among sign languages, while providing a first step for synthesizing those aspects that are different. Further, it suggests a possible path forward to exploring whether linguistic structures in one sign language can be exploited in other sign languages, which might be particularly helpful in under-resourced languages. © 2024 ELRA language Resources Association: CC BY-NC 4.0.

关键词： Animation

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Collaborative Metadata Aggregation and Curation in Support of Digital language Equality Monitoring

Collaborative Metadata Aggregation and Curation in Support o...

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2022 Towards Digital language Equality Workshop, TDLE 2022

作者： Giagkou, Maria Labropoulou, Penny Piperidis, Stelios Deligiannis, Miltos Kolovou, Athanasia Voukoutis, Leon Institute for Language and Speech Processing Athena Research Centre Greece

ISBN: (纸本)9782493814036

The European language Equality (ELE) project develops a strategic research, innovation and implementation agenda (SRIA) and a roadmap for achieving full digital language equality in Europe by 2030. Key component of the SRIA development is an accurate estimation of the current standing of languages with respect to their technological readiness. In this paper we present the empirical basis on which such estimation is grounded, its starting point and in particular the automatic and collaborative methods used for extending it. We focus on the collaborative expert activities, the challenges posed, and the solutions adopted. We also briefly present the dashboard application developed for querying and visualising the empirical data as well as monitoring and comparing the evolution of technological support within and across languages. © European language Resources Association (ELRA), licensed under CC-BY-NC-4.0.

关键词： Metadata

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Towards Systematic Monolingual NLP Surveys: GenA of Greek NLP

arXiv

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arXiv 2024年

作者： Bakagianni, Juli Pouli, Kanella Gavriilidou, Maria Pavlopoulos, John Institute for Language and Speech Processing Athena RC Greece Athens University of Economics and Business Archimedes/Athena RC Greece Stockholm University Sweden

Natural language processing (NLP) research has traditionally been predominantly focused on English, driven by the availability of resources, the size of the research community, and market demands. Recently, there has been a noticeable shift towards multilingualism in NLP, recognizing the need for inclusivity and effectiveness across diverse languages and cultures. Monolingual surveys have the potential to complement the broader trend towards multilingualism in NLP by providing foundational insights and resources, necessary for effectively addressing the linguistic diversity of global communication. However, monolingual NLP surveys are extremely rare in the literature. This study introduces a generalizable methodology for creating systematic and comprehensive monolingual NLP surveys, aimed at optimizing the process of constructing such surveys and thoroughly addressing a language’s NLP support. Our approach integrates a structured search protocol to avoid selection bias and ensure reproducibility, an NLP task taxonomy to organize the surveyed material coherently, and language resources (LRs) taxonomies to identify potential benchmarks and highlight opportunities for improving resource availability (e.g., through better maintenance or licensing). We apply this methodology to Greek NLP (2012-2023), providing a comprehensive overview of its current state and challenges. We discuss the progress of Greek NLP and outline the Greek LRs found, classified by availability and usability, assessing language support per NLP task. The presented systematic literature review of Greek NLP serves as an application of our method that showcases the benefits of monolingual NLP surveys more broadly. Similar applications could be considered for the myriads of languages whose progress in NLP lags behind that of well-supported languages. © 2024, CC BY.

关键词： Taxonomies

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The EASIER Mobile Application and Avatar End-User Evaluation Methodology 11

The EASIER Mobile Application and Avatar End-User Evaluation...

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11th Workshop on the Representation and processing of Sign languages: Evaluation of Sign language Resources, sign-lang@LREC-COLING 2024

作者： Picron, Frankie Van Landuyt, Davy Omardeen, Rehana Efthimiou, Eleni Wolfe, Rosalee Fotinea, Stavroula-Evita Goulas, Theodore Tismer, Christian Kopf, Maria Hanke, Thomas European Union of the Deaf Belgium Institute for Language and Speech Processing ATHENA Research Center Greece Nuromedia GmbH Germany Institute of German Sign Language and Communication of the Deaf University of Hamburg Germany

ISBN: (纸本)9782493814302

Here we report on the methodological approach adopted for the end-user evaluation studies carried out during the lifecycle of the EASIER project, focusing on the project's mobile app and avatar technologies. Evaluation was led by deaf consortium partners and performed in two cycles, involving both deaf signers and hearing sign language (SL) experts groups from five SLs to provide user feedback, which served as a reference to base the next development steps of the respective EASIER components. With this goal in mind, priorities were (i) to exploit information gathered via focus group discussions after (ii) presenting evaluators with the technological components and related questionnaires fully accessible to signers to maximize feedback and underline the importance of user involvement in the development of the technology. © 2024 ELRA language Resources Association: CC BY-NC 4.0.

关键词： Audition

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Exploring language-Agnostic speech Representations Using Domain Knowledge for Detecting Alzheimer's Dementia 48

Exploring Language-Agnostic Speech Representations Using Dom...

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48th IEEE International Conference on Acoustics, speech and Signal processing, ICASSP 2023

作者： Shah, Zehra Qi, Shi-Ang Wang, Fei Farrokh, Mahtab Tasnim, Mashrura Stroulia, Eleni Greiner, Russell Plitsis, Manos Katsamanis, Athanasios University of Alberta Department of Computing Science Edmonton Canada Athena Research Center Institute for Language and Speech Processing Greece

ISBN: (纸本)9781728163277

We explore ways to use speech data to screen for indications of Alzheimer's dementia (AD). In particular, we describe our approach to the ICASSP 2023 Signal processing Grand Challenge, which involves extrapolating from models learned from English speech samples, to Greek speech samples, to determine which subjects have AD. By using acoustic and linguistic features, inspired by clinical research on AD, our top-performing classification model achieves 69% accuracy in distinguishing AD patients from healthy controls, and our regression model attains an RMSE of 4.8 for inferring cognitive testing scores. These outcomes underscore the potential of our explainable model for detecting cognitive decline in AD patients via speech, and its applicability in clinical settings. © 2023 IEEE.

关键词： Alzheimer's dementia Machine Learning Signal processing speech

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Adapted Multimodal Bert with Layer-Wise Fusion for Sentiment Analysis 48

Adapted Multimodal Bert with Layer-Wise Fusion for Sentiment...

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48th IEEE International Conference on Acoustics, speech and Signal processing, ICASSP 2023

作者： Chlapanis, Odysseas S. Paraskevopoulos, Georgios Potamianos, Alexandros National Technical University of Athens Athens Greece Institute for Language and Speech Processing Athena Research Center Athens Greece

ISBN: (纸本)9781728163277

Multimodal learning pipelines have benefited from the success of pretrained language models. However, this comes at the cost of increased model parameters. In this work, we propose Adapted Multimodal BERT (AMB), a BERT-based architecture for multimodal tasks that uses a combination of adapter modules and intermediate fusion layers. The adapter adjusts the pretrained language model for the task at hand, while the fusion layers perform task-specific, layer-wise fusion of audio-visual information with textual BERT representations. During the adaptation process the pre-trained language model parameters remain frozen, allowing for fast, parameter-efficient training. In our ablations we see that this approach leads to efficient models, that can outperform their fine-tuned counterparts and are robust to input noise. Our experiments on sentiment analysis with CMU-MOSEI show that AMB outperforms the current state-of-the-art across metrics, with 3.4% relative reduction in the resulting error and 2.1% relative improvement in 7-class classification accuracy. © 2023 IEEE.

关键词： adapters BERT fusion multimodal

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