Hand and Mind: What Gestures Reveal about Thought. David McNeill. Chicago and London: University of Chicago Press, 1992. 416 pp.

Hand and Mind: What Gestures Reveal about Thought

Abstract The Metaverse has been the centre of attraction for educationists for quite some time. This field got renewed interest with the announcement of social media giant Facebook as it rebranding and positioning it as Meta. While several studies conducted literature reviews to summarize the findings related to the Metaverse in general, no study to the best of our knowledge focused on systematically summarizing the finding related to the Metaverse in education. To cover this gap, this study conducts a systematic literature review of the Metaverse in education. It then applies both content and bibliometric analysis to reveal the research trends, focus, and limitations of this research topic. The obtained findings reveal the research gap in lifelogging applications in educational Metaverse. The findings also show that the design of Metaverse in education has evolved over generations, where generation Z is more targeted with artificial intelligence technologies compared to generation X or Y. In terms of learning scenarios, there have been very few studies focusing on mobile learning, hybrid learning, and micro learning. Additionally, no study focused on using the Metaverse in education for students with disabilities. The findings of this study provide a roadmap of future research directions to be taken into consideration and investigated to enhance the adoption of the Metaverse in education worldwide, as well as to enhance the learning and teaching experiences in the Metaverse. 

/pdf/is-metaverse-in-education-a-blessing-or-a-curse-a-combined-39ocoj1r.pdf

Is Metaverse in education a blessing or a curse: a combined content and bibliometric analysis

Sentiment analysis is a growing field at the intersection of linguistics and computer science that attempts to automatically determine the sentiment contained in text. Sentiment can be characterized as positive or negative evaluation expressed through language. Common applications of sentiment analysis include the automatic determination of whether a review posted online (of a movie, a book, or a consumer product) is positive or negative toward the item being reviewed. Sentiment analysis is now a common tool in the repertoire of social media analysis carried out by companies, marketers, and political analysts. Research on sentiment analysis extracts information from positive and negative words in text, from the context of those words, and from the linguistic structure of the text. This brief review examines in particular the contributions that linguistic knowledge can make to the task of automatically determining sentiment.

/pdf/sentiment-analysis-an-overview-from-linguistics-4c4gnd1edx.pdf

Sentiment Analysis: An Overview from Linguistics

While advanced text generation algorithms (e.g., GPT-3) have enabled writers to co-create stories with an AI, guiding the narrative remains a challenge. Existing systems often leverage simple turn-taking between the writer and the AI in story development. However, writers remain unsupported in intuitively understanding the AI’s actions or steering the iterative generation. We introduce TaleBrush, a generative story ideation tool that uses line sketching interactions with a GPT-based language model for control and sensemaking of a protagonist’s fortune in co-created stories. Our empirical evaluation found our pipeline reliably controls story generation while maintaining the novelty of generated sentences. In a user study with 14 participants with diverse writing experiences, we found participants successfully leveraged sketching to iteratively explore and write stories according to their intentions about the character’s fortune while taking inspiration from generated stories. We conclude with a reflection on how sketching interactions can facilitate the iterative human-AI co-creation process.

TaleBrush: Sketching Stories with Generative Pretrained Language Models

This book introduces the concept of information sharing as an area of cognitive science, defining it as the process by which speakers depend on "given" information to convey "new" information - an idea crucial to language engineering. Where previous work in information sharing was often fragmented between different disciplines, this volume brings together theoretical and applied work and joins computational contributions with papers based on analyses of language corpora and on psycholinguistic experimentation.

Information sharing : reference and presupposition in language generation and interpretation

Due to the critical role that normalisation plays during the translation and localisation processes, we propose here to analyse some standards, as well as the related software tools that are used by professional translators and by several automatic translating services. We will first point out the importance of normalisation within the translation and localisation activities. Next, we will introduce a methodology of standardisation, whose objective is to harmonise the management and the representation of multilingual data. The control of the interoperability between the industrial standards currently used for localisation [XLIFF], translation memory [TMX], or with some recent initiatives such as the internationalisation tag set [ITS], constitutes a major objective for a coherent and global management of multilingual data. The Multi Lingual Information Framework MLIF [ISO AWI 24616] is based on a methodology of standardisation resulting from the ISO (sub-committees TC37/SC3 “Computer Applications for Terminology” and SC4 “Language Resources Management”). MLIF aims at proposing a high-level abstract specification platform for a computer-oriented representation of multilingual data within a large variety of applications such as translation memories, localisation, computer-aided translation, multimedia, or electronic document management. The major benefit of MLIF is interoperability because it allows experts to gather, under the same conceptual model, various tools and representations related to multilingual data. In addition, MLIF should also make it possible to evaluate and to compare these multilingual resources and tools.

https://hal.inria.fr/inria-00105653/document

10. Standardising the management and the representation of multilingual data: The Multi Lingual Information Framework

The study presented in this paper is dedicated to the integration of pointing gestures within a task oriented man-machine dialogue system. From our point of view, it is natural to see this problem as a sub-part of the more general study of reference in a dialogue since we took the option to limit the analysis of gestures to those explicitly associated with speech and more specifically for singling out objects in the task. Even under these hypotheses, understanding the global message resulting from the combinaison of speech and gesture implies that a precise analysis of the gestural trajectory should be done. This analysis may be split up into two main steps. The first, which we may call structural, is centred upon the shape of the gestural trajectory to mark the meaningful parts to which a specific designation role will be given. The second step has to do with the contextual interpretation of the gesture for which one has to take into account a) the features of the application and the way it is visualized and b) the oral dialogue and more specifically the instructional content of the referring expression accompanying the gesture.

https://hal.archives-ouvertes.fr/hal-00521585/document

Reference interpretation in a multimodal environment combining speech and gesture

Within a globalized world, the need for linguistic support is increasing every day. Linguistic information, and in particular multilingual textual information, plays a significant role for describing digital content: information describing pictures or video sequences, general information presented to the user graphically or via a text-to-speech processor, menus in interactive multimedia or TV, subtitles, dialogue prompts, or implicit data appearing on an image such as captions, or tags. It is obviously crucial to associate digital content to linguistic information in a non-intrusive way: the user must decide, whether or not, he wants to display the linguistic information related to the digital content he is dealing with in any particular language. 
In this chapter we will present a general review on linguistic and multilingual issues related to virtual worlds and serious games. The expression “linguistic and multilingual issues” will consider not only any kind of linguistic support (such as syntactic and semantic analysis) based on textual information, but also any kind of multilingual and monolingual topics (such as localization or automatic translation), and their association to virtual worlds and serious games. We will focus on our ongoing research activities, particularly in the framework of sentiment analysis and emotion detection. Note that we will also dedicate special attention to standardization issues because they grant interoperability, stability, and durability.
The review will essentially be based on our own experience but some interesting international research projects and applications will be also mentioned, in particular, research projects and applications related to sentiment analysis and emotion detection.

Handbook on 3D3C Platforms: Applications and Tools for Three Dimensional Systems for Community, Creation and Commerce

Virtual Worlds may become primary tools (with video and text secondary) for learning many aspects of history, for acquiring new skills, for job assessment, and for many of our most cost-effective and productive forms of collaboration (Metaverse Roadmap Repport, 2007).

	We propose a non-intrusive and dynamic e-learning-oriented scenario based on textual information. This scenario exemplifies how a standardized framework for textual multilingual support associated to an immersive 3D environment, may considerably change the way people usually deal with multilingual information and with language learning on the Internet.

/pdf/immersive-3d-environments-and-multilinguality-a-non-21hqt0oh6k.pdf

Immersive 3D environments and Multilinguality: A Non-Intrusive and Dynamic e-learning-Oriented Scenario based on Textual Information

Textual sentiment analysis and emotion detection consists in retrieving the sentiment or emotion carried by a text or document. This task can be useful in many domains: opinion mining, prediction, feedbacks, etc. However, building a general purpose tool for doing sentiment analysis and emotion detection raises a number of issues, theoretical issues like the dependence to the domain or to the language but also pratical issues like the emotion representation for interoperability. In this paper we present our sentiment/emotion analysis tools, the way we propose to circumvent the di culties and the applications they are used for.

pdf/general-purpose-textual-sentiment-analysis-and-emotion-47bveiwlnm.pdf

General Purpose Textual Sentiment Analysis and Emotion Detection Tools

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