Analyzing collaborative learning processes automatically

In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a publicly available tool set called TagHelper tools. Analyzing the variety of pedagogically valuable facets of learners’ interactions is a time consuming and effortful process. Improving automated analyses of such highly valued processes of collaborative learning by adapting and applying recent text classification technologies would make it a less arduous task to obtain insights from corpus data. This endeavor also holds the potential for enabling substantially improved on-line instruction both by providing teachers and facilitators with reports about the groups they are moderating and by triggering context sensitive collaborative learning support on an as-needed basis. In this article, we report on an interdisciplinary research project, which has been investigating the effectiveness of applying text classification technology to a large CSCL corpus that has been analyzed by human coders using a theory-based multidimensional coding scheme. We report promising results and include an in-depth discussion of important issues such as reliability, validity, and efficiency that should be considered when deciding on the appropriateness of adopting a new technology such as TagHelper tools. One major technical contribution of this work is a demonstration that an important piece of the work towards making text classification technology effective for this purpose is designing and building linguistic pattern detectors, otherwise known as features, that can be extracted reliably from texts and that have high predictive power for the categories of discourse actions that the CSCL community is interested in

Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation

This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input. A survey of NLG is timely in view of the changes that the field has undergone over the past decade or so, especially in relation to new (usually data-driven) methods, as well as new applications of NLG technology. This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of relatively recent research topics that have arisen partly as a result of growing synergies between NLG and other areas of artificial intelligence; (c) draw attention to the challenges in NLG evaluation, relating them to similar challenges faced in other areas of Natural Language Processing, with an emphasis on different evaluation methods and the relationships between them.Comment: Published in Journal of AI Research (JAIR), volume 61, pp 75-170. 118 pages, 8 figures, 1 tabl

Web augmentation of language models for continuous speech recognition of SMS text messages

In this paper, we present an efficient query selection algorithm for the retrieval of web text data to augment a statistical language model (LM). The number of retrieved relevant documents is optimized with respect to the number of queries submitted. The querying scheme is applied in the domain of SMS text messages. Continuous speech recognition experiments are conducted on three languages: English, Spanish, and French. The web data is utilized for augmenting in-domain LMs in general and for adapting the LMs to a user-specific vocabulary. Word error rate reductions of up to 6.6 % (in LM augmentation) and 26.0 % (in LM adaptation) are obtained in setups, where the size of the web mixture LM is limited to the size of the baseline in-domain LM.Peer reviewe

META-NET Strategic Research Agenda for Multilingual Europe 2020

In everyday communication, Europe’s citizens, business partners and politicians are inevitably confronted with language barriers. Language technology has the potential to overcome these barriers and to provide innovative interfaces to technologies and knowledge. This document presents a Strategic Research Agenda for Multilingual Europe 2020. The agenda was prepared by META-NET, a European Network of Excellence. META-NET consists of 60 research centres in 34 countries, who cooperate with stakeholders from economy, government agencies, research organisations, non-governmental organisations, language communities and European universities. META-NET’s vision is high-quality language technology for all European languages. “The research carried out in the area of language technology is of utmost importance for the consolidation of Portuguese as a language of global communication in the information society.” — Dr. Pedro Passos Coelho (Prime-Minister of Portugal) “It is imperative that language technologies for Slovene are developed systematically if we want Slovene to flourish also in the future digital world.” — Dr. Danilo Türk (President of the Republic of Slovenia) “For such small languages like Latvian keeping up with the ever increasing pace of time and technological development is crucial. The only way to ensure future existence of our language is to provide its users with equal opportunities as the users of larger languages enjoy. Therefore being on the forefront of modern technologies is our opportunity.” — Valdis Dombrovskis (Prime Minister of Latvia) “Europe’s inherent multilingualism and our scientific expertise are the perfect prerequisites for significantly advancing the challenge that language technology poses. META-NET opens up new opportunities for the development of ubiquitous multilingual technologies.” — Prof. Dr. Annette Schavan (German Minister of Education and Research

Survey on Evaluation Methods for Dialogue Systems

In this paper we survey the methods and concepts developed for the evaluation of dialogue systems. Evaluation is a crucial part during the development process. Often, dialogue systems are evaluated by means of human evaluations and questionnaires. However, this tends to be very cost and time intensive. Thus, much work has been put into finding methods, which allow to reduce the involvement of human labour. In this survey, we present the main concepts and methods. For this, we differentiate between the various classes of dialogue systems (task-oriented dialogue systems, conversational dialogue systems, and question-answering dialogue systems). We cover each class by introducing the main technologies developed for the dialogue systems and then by presenting the evaluation methods regarding this class

Bootstrapping Information from Corpora in a Cross-Linguistic Perspective

The achievements of Romance language corpus-driven studies deserve more attention from the scientific community at the world level for both their quantity and quality. This book contains papers given at the 3rd International LABLITA Workshop in Corpus Linguistics (Italian Department, University of Florence, June 4th-5th 2008 ), and it aims at integrating new ideas and results derived from Romance language corpora in the framework of the overall achievements of Corpus Linguistics. The volume contains the contribution of a leading scholar of Corpus Linguistics (Douglas Biber), and a set of articles presented to Biber by notable European researchers and those from other countries. Papers report on long-term studies ranging from Italian to Spanish, French, Brazilian Portuguese and Japanese