The main RANLP conference will be preceeded by three days tutorials delivered by distinguished lecturers. We plan 6 half day tutorials, each with duration of 220 minutes, distributed as follows: 60 min talk + 20 min break + 60 min talk + 20 min break + 60 min talk.
Tutorial lectureres:
Elisabeth Andre (University of Augsburg)
Dimitar Kazakov (University of York)
Bernardo Magnini (FBK-irst, Trento)
Stelios Piperidis (ILSP Athens)
Frederique Segond (Xerox Research Centre Grenoble)
Karin Verspoor (Los Alamos National Laboratory)
& Kevin Bretonnel Cohen (University of Colorado School of Medicine)
Tutorial timetable is as follows:
Abstracts
Speech-Based Multimodal Dialogue
Elisabeth Andre, University of Augsburg
The tutorial focuses on speech-based dialogue systems that emulate
aspects of human-human communication by making use of embodied
conversational agents. These agents display facial expressions, gaze
patterns, head, hand and arm gestures in synchrony with their speech.
While work on speech-based dialogue is usually driven by the objective
to achieve a high amount of robustness and efficiency, researchers
working on embodied conversational agents also need to address aspects
of social communication, such as emotions and personality. The tutorial
provides an overview of approaches to determine multimodal dialogue acts
for a single agent as well as agent teams conversing with one or
several human users. We will discuss how dialogue management tools need
to extended to account for the challenges of multimodal multi-party
dialogue. To emulate human face-to-face dialogue more closely, it is
desirable to avoid asymmetries in communication channels. A specific
part of the tutorial is therefore devoted to first attempts towards the
development of perceptive agents which are able to perceive
communicative feedback signals from the human conversational partner.
Information Retrieval
Dimitar Kazakov, University of York
The area of Information Retrieval (IR) studies the techniques used to
detect the existence and find the whereabouts of one or more documents
related to a request. This includes the services provided by search
engines, but traditionally excludes Question-Answering systems. The
tutorial will cover, and consistently demonstrate on working examples, the
technology behind the currently used tools for information retrieval, be
it online search engines or local (single machine, local net) solutions.
Textual Entailment
Bernardo Magnini, FBK-irst, Trento
The goal of identifying textual entailment - whether one piece of ?text can be plausibly inferred from another - has emerged in recent ?years as a generic core problem in Natural Language Understanding. For instance, in order to answer the question 'Who killed Kennedy?', a Question Answering system may need to recognize that 'Oswald killed Kennedy' can be inferred from 'the assassination of Kennedy by Oswald'. This challenge is at the heart of many natural language understanding tasks including Question Answering, Information Retrieval and Extraction, Machine Translation, and others that attempt to reason about and capture the meaning of linguistic expressions. The task has attracted significant interest over the last couple of years mainly fostered by the PASCAL Recognizing Textual Entailment Challenge (RTE).
The primary goals of this tutorial are to review the framework of applied Textual Entailment and motivate it as a generic paradigm for natural language semantics. The tutorial will provide a concise overview of recent perspectives and research results and present some of the key computational approaches proposed and some of the obstacles identified by the research community in this area.
Multimedia Content Processing and Applications
Stelios Piperidis – ILSP, Athens
The convergence of technological communication platforms opens up new opportunities for content generation and consumption, while enabling such content to be increasingly multimedia in nature. This tutorial will provide an introduction to multimedia content processing, focusing on the role and significance of natural language in multimedia discourse. We will briefly review the state-of-the-art in single-media processing (speech, text, video, etc) and discuss the problems, challenges, fall-back solutions and necessities for further advances. The role of the different media and the potential benefit from comparative analysis and fusion of single-media processing results will be discussed in the context of different applications. Current achievements and practical applications involving archived or contemporary, monolingual or multilingual multimedia content will be illustrated by working examples.
Industrial developments in NLP
Frederique Segond, Xerox Research Centre Europe
This tutorial will examine the role of NLP and in particular of NLP
research from an industrial perspective. Specifically, using real
examples from the industry, it will focus on issues and concerns that must
be addressed to meet the needs of potential customers for NLP technology.
This includes issues such as: is industrial research different from
academic reserach in NLP? What does industry wants from NLP? Is the demand
changing? What are the vertical markets? What are the technical
constraints? Validation of NLP technology in an industrial context.
Natural Language Processing and the Biomedical domain
K. Bretonnel Cohen, University of Colorado School of Medicine and Karin Verspoor, Los Alamos National Laboratory
This tutorial will provide natural language processing researchers with an
introduction to the field of іBioNLPІ -- natural language processing in
the fields of medicine and biology. This field has long roots in the
history of natural language processing, but has been an absolutely
burgeoning field of interest in recent years. The past few years have been
characterized by an unusual mixing of bioinformatics and NLP specialists
at the conferences of both communities: ACL or NAACL has now hosted
workshops on BioNLP every year since 2002, with excellent attendance
numbers, and bioinformatics and medical informatics meetings have featured
NLP papers, sessions, and SIG meetings since the late 1990s. Recent
MUC-like and TREC-sponsored shared tasks have had some unusual results,
and the implications of these findings should make for an interesting
tutorial for the general NLP researcher.
BioNLP presents unique challenges in a number of areas, ranging from
low-level processing tasks to high-level conceptual issues. Tokenization
and sentence boundary detection are demonstrably different tasks in
biomedical publications than in newswire text, and theoretical issues such
as predicate-argument structure representation have been a topic of much
discussion in recent work in the field. Despite the many challenges that
are unique to biomedical text, most of the sub-topics of NLP are the
subject of current research in the BioNLP community -- information
retrieval, named entity recognition, information extraction, text
classification, semantic role labeling, coreference resolution,
question-answering, parsing, morphological analysis, and discourse
analysis. Thus, there are interesting challenges in the biomedical domain
for almost anyone working in natural language processing.
One unique advantage to the field of BioNLP is the wide availability of
biological knowledge resources, including an enormous body of freely
available text. The tutorial will include an overview of a variety of
publicly available BioNLP resources, including:
* A number of domain-specific ontologies, including the popular Gene
Ontology
* Corpora, including the popular GENIA corpus and a number of
less-well-known but valuable corpora and text collections, some of them
featuring full text
One potential stumbling block in the field of BioNLP is the requirement
for domain knowledge. The tutorial will include a brief overview of just
enough biology to enable the NLP researcher to comprehend the topics under
discussion in typical biomedical texts, if not the specifics of the
discussion.
|