Total Articles: 38870

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 162

This paper describes a framework for the creation of new derivational morphology databases for a selected set of productive af- fixes in English. The sample resource ob- tained comprises almost 120k English words with morpheme segmentations generated by Transformer. The model and the database have been compared against other existing …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16252

AbstractIn this paper we present SHARE, a new lexical resource with 10,125 offensive terms and expressions collected from Spanish speakers. We retrieve this vocabulary using an existing chatbot developed to engage a conversation with users and collect insults via Telegram, named Fiero. This vocabulary has been manually labeled by five …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16253

AbstractIn dialogue analysis, characterising named entities in the domain of interest is relevant in order to understand how people are making use of them for argumentation purposes. The movie recommendation domain is a frequently considered case study for many applications and by linguistic studies and, since many different resources have …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16254

AbstractEvery model is only as strong as the data that it is trained on. In this paper, we present a new dataset, obtained by merging four publicly available annotated corpora for task-oriented dialogues in several domains (MultiWOZ 2.2, CamRest676, DSTC2 and Schema-Guided Dialogue Dataset). This way, we assess the feasibility …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16255

AbstractIn human-human conversations, Context Tracking deals with identifying important entities and keeping track of their properties and relationships. This is a challenging problem that encompasses several subtasks such as slot tagging, coreference resolution, resolving plural mentions and entity linking. We approach this problem as an end-to-end modeling task where the …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16256

AbstractSeveral dialogue corpora are currently available for research purposes, but they still fall short for the growing interest in the development of dialogue systems with their own specific requirements. In order to help those requiring such a corpus, this paper surveys a range of available options, in terms of aspects …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16257

AbstractDialog system developers need high-quality data to train, fine-tune and assess their systems. They often use crowdsourcing for this since it provides large quantities of data from many workers. However, the data may not be of sufficiently good quality. This can be due to the way that the requester presents …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16258

AbstractOften both an utterance and its context must be read to understand its intent in a dialog. Herein we propose a task, Self- Contained Utterance Description (SCUD), to describe the intent of an utterance in a dialog with multiple simple natural sentences without the context. If a task can be …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16259

AbstractWe propose a deep learning-based foreign language learning platform, named FreeTalky, for people who experience anxiety dealing with foreign languages, by employing a humanoid robot NAO and various deep learning models. A persona-based dialogue system that is embedded in NAO provides an interesting and consistent multi-turn dialogue for users. Also, …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16260

AbstractSpeech interfaces for argumentative dialogue systems (ADS) are rather scarce. The complex task they pursue hinders the application of common natural language understanding (NLU) approaches in this domain. To address this issue we include an adaption of a recently introduced NLU framework tailored to argumentative tasks into a complete ADS. …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16261

AbstractIn this paper, we present the FABRA: readability toolkit based on the aggregation of a large number of readability predictor variables. The toolkit is implemented as a service-oriented architecture, which obviates the need for installation, and simplifies its integration into other projects. We also perform a set of experiments to …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16262

AbstractCAMIO (Corpus of Annotated Multilingual Images for OCR) is a new corpus created by Linguistic Data Consortium to serve as a resource to support the development and evaluation of optical character recognition (OCR) and related technologies for 35 languages across 24 unique scripts. The corpus comprises nearly 70,000 images of …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16263

AbstractWe present the development of a benchmark suite consisting of an annotation schema, training corpus and baseline model for Entity Recognition (ER) in job descriptions, published under a Creative Commons license. This was created to address the distinct lack of resources available to the community for the extraction of salient …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16264

AbstractIn this paper, we describe the creation and annotation of EPIC UdS, a multilingual corpus of simultaneous interpreting for English, German and Spanish. We give an overview of the comparable and parallel, aligned corpus variants and explore various applications of the corpus. What makes EPIC UdS relevant is that it …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16265

AbstractWe present an analysis pipeline and best practice guidelines for building and curating corpora of everyday conversation in diverse languages. Surveying language documentation corpora and other resources that cover 67 languages and varieties from 28 phyla, we describe the compilation and curation process, specify minimal properties of a unified format …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16266

AbstractMachine learning (ML) approaches have dominated NLP during the last two decades. From machine translation and speech technology, ML tools are now also in use for spellchecking and grammar checking, with a blurry distinction between the two. We unmask the myth of effortless big data by illuminating the efforts and …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16267

AbstractWord embeddings (Mikolov et al., 2013; Pennington et al., 2014) have been used to bolster the performance of natural language processing systems in a wide variety of tasks, including information retrieval (Roy et al., 2018) and machine translation (Qi et al., 2018). However, approaches to learning word embeddings typically require …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16268

AbstractWe present the TeDDi sample, a diversity sample of text data for language comparison and multilingual Natural Language Processing. The TeDDi sample currently features 89 languages based on the typological diversity sample in the World Atlas of Language Structures. It consists of more than 20k texts and is accompanied by …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16269

AbstractOur work aims at developing a multilingual data resource for morphological segmentation. We present a survey of 17 existing data resources relevant for segmentation in 32 languages, and analyze diversity of how individual linguistic phenomena are captured across them. Inspired by the success of Universal Dependencies, we propose a harmonized …...

nan

Publication: TIPSTER (2022)

DOI: nan

Paper ID: 16270

AbstractIn this paper we present the final result of a project focused on Tunisian Arabic encoded in Arabizi, the Latin-based writing system for digital conversations. The project led to the realization of two integrated and independent tools: a linguistic corpus and a neural network architecture created to annotate the former …...