Explanation of three Research Topics (Q.2) 2nd theme

22 04 2008

In this article, I am going to explain three of different research topics that I have chosen between the others.

The first topic I’m going to talk about is “NECA” or “Net Environment for Embodied Emotional Conversational Agents” one of previous projects of the Austrian Research Institute for Artificial Intelligence ÖFAI.

In the NECA project, the focus is on the design of credible agent-agent interaction patterns to be observed by human users. To achieve a high level of credibility, the agents must be able to express themselves using a combination of verbal and non-verbal output driven by personality and emotion models.

Moreover, the NECA project will develop a new generation of mixed multi-user / multi-agent virtual spaces populated by affective conversational agents. The agents will be able to express themselves through synchronised emotional speech and non-verbal behaviour, generated from an abstract representation which can be the output of an affective reasoner. This is the first time that such expressive capabilities are featured in Internet applications. The agents’ usefulness will be evaluated in two concrete application scenarios. From a technical point of view, the emerging NECA platform will provide a confederation of dedicated components including an affective reasoner, co-ordinated generation, and emotional speech synthesis, thus providing a basis for the development of new Internet applications with emotional agents.

The next research topic I am going to explain is “HUMAINE” or “Human-machine Interaction Network on Emotions”.

HUMAINE aims to lay the foundations for European development of systems that can register, model and/or influence human emotional and emotion-related states and processes – ‘emotion-oriented systems’. Such systems may be central to future interfaces, but their conceptual underpinnings are not sufficiently advanced to be sure of their real potential or the best way to develop them.

In addition, one of the reasons is that relevant knowledge is dispersed across many disciplines. HUMAINE brings together leading experts from the key disciplines in a programme designed to achieve intellectual integration. It identifies six thematic areas that cut across traditional groupings and offer a framework for an appropriate division of labour – theory of emotion; signal/sign interfaces; the structure of emotionally coloured interactions; emotion in cognition and action; emotion in communication and persuasion; and usability of emotion-oriented systems. Teams linked to each area will run a workshop in it and carry out joint research to define an exemplar embodying guiding principles for future work in their area.

Finally, the last research topic which I will focus on is Corpus Linguistics:

Corpus Linguistics is the study of linguistic phenomena through large collections of machine-readable texts: corpora. These are used within a number of research areas going from the Descriptive Study of the Syntax of a Language to Prosody or Language Learning, to mention but a few. An over-view of some of the areas where corpora have been used can be found on the Research areas page.

Furthermore, the use of real examples of texts in the study of language is not a new issue in the history of linguistics. However, Corpus Linguistics has developed considerably in the last decades due to the great possibilities offered by the processing of natural language with computers. The availability of computers and machine-readable text has made it possible to get data quickly and easily and also to have this data presented in a format suitable for analysis.


* “NECA” or “Net Environment for Embodied Emotional Conversational Agents”. Retrieved, 18:34, 21th April 2008 from, http://www.dfki.de/pas/f2w.cgi?ltc/neca-e

* “NECA” or “Net Environment for Embodied Emotional Conversational Agents”. Retrieved, 19:02, 21th April 2008 from, http://www.ofai.at/~brigitte.krenn/papers/web3d_krenn_paper.pdf

* “HUMAINE” or “Human-machine Interaction Network on Emotions”. Retrieved, 17: 14, 18th April 2008 from, http://www.dfki.de/pas/f2w.cgi?ltp/humaine-e

* Corpus Linguistics. Retrieved, 17:22, 18th April 2008 from, http://www.essex.ac.uk/linguistics/clmt/w3c/corpus_ling/content/introduction3.html

Research Topics (Q.2) 1st theme

16 04 2008

In this article I will point out some research topics that are mentioned on different sites of Human Language Technologies.

Firstly, members of The Stanford NLP Group pursue research in a broad variety of topics:

  • Computational Semantics.
  • Parsing & Tagging.
  • Multilingual NLP.
  • Unsupervised Induction of Linguistic Structure.

Secondly, in Edinburgh Language Technology Group of Scotland, UK we can mention some of their projects which conducts research and development in a number of areas.

  • Combining Shallow Semantics and Domain Knowledge.
  • Text Mining fot Biomedical Content Curation.
  • Cross-retail Multi-agent Retail Comparison.
  • Smart Qualitative Data: Methods and Community Tools for Data Mark-Up.
  • Machine Learning for Named Entity Recognition.
  • Named entity tagging of historical parliamentary proceedings.
  • Integrated Models and Tolls for Fine-Grained Prosody in Discourse.
  • Joint Action Science and Technology.
  • AMI consortium projects that are developing technologies for meeting browsing and to assist people participating in meetings from a remote location.
  • Study of how pairs collaborate when in planning a route on a map.

Finally, we can mention the German Language Technology Lab, which themes are elaborated in research, development and commercial projects:

  • Exploiting – and automatically extending – ontologies for content processing.
  • Tighter integration of shallow and deep techniques in processing.
  • Enriching deep processing with statistical methods.
  • Combining language checking with structuring tools in document authoring.
  • Document indexing for German and English.
  • Automatically associating recognized information with related information and thus building up collective knowledge.
  • Automatically structuring and visualizing extracted information.
  • Processing information encoded in multiple languages, among them Chinese and Japanese.