Nick Webb

Modeling Sociocultural phenomena in discourse

In this paper, we describe a novel approach to computational modeling and understanding of social and cultural phenomena in multi-party dialogues. We developed a two-tier approach in which we first detect and classify certain sociolinguistic behaviors, including topic control, disagreement, and involvement, that serve as first-order models from which presence the higher level social roles, such as leadership, may be inferred.

Data-Driven Strategies for an Automated Dialogue System

We present a prototype natural-language problem-solving application for a financial services call center, developed as part of the Amities multilingual human-computer dialogue project. Our automated dialogue system, based on empirical evidence from real call-center conversations, features a data-driven approach that allows for mixed system/customer initiative and spontaneous conversation. Preliminary evaluation results indicate efficient dialogues and high user satisfaction, with performance comparable to or better than that of current conversational travel information systems.

Interaction strategies for an affective conversational agent

The development of embodied conversational agents (ECA) as companions brings several challenges for both affective and conversational dialogue. These include challenges in generating appropriate affective responses, selecting the overall shape of the dialogue, providing prompt system response times, and handling interruptions. We present an implementation of such a companion showing the development of individual modules that attempt to address these challenges. Further, to resolve resulting conflicts, we present encompassing interaction strategies that attempt to balance the competing requirements along with dialogues from our working prototype to illustrate these interaction strategies in operation. Finally, we provide the results of an evaluation of the companion using an evaluation methodology created for conversational dialogue and including analysis using appropriateness annotation.

Using imageability and topic chaining to locate metaphors in linguistic corpora

The reliable automated identification of metaphors still remains a challenge in metaphor research due to ambiguity between semantic and contextual interpretation of individual lexical items. In this article, we describe a novel approach to metaphor identification which is based on three intersecting methods: imageability, topic chaining, and semantic clustering. Our hypothesis is that metaphors are likely to use highly imageable words that do not generally have a topical or semantic association with the surrounding context. Our method is thus the following: (1) identify the highly imageable portions of a paragraph, using psycholinguistic measures of imageability, (2) exclude imageability peaks that are part of a topic chain, and (3) exclude imageability peaks that show a semantic relationship to the main topics. We are currently working towards fully automating this method for a number of languages.

Error analysis of dialogue act classification

We are interested in the area of Dialogue Act (da) tagging. Identifying the dialogue acts of utterances is recognised as an important step towards understanding the content and nature of what speakers say. We have built a simple dialogue act classifier based on purely intra-utterance features – principally word n-gram cue phrases. Although such a classifier performs surprisingly well, rivalling scores obtained using far more sophisticated language modelling techniques for the corpus we address, we want to understand further the issues raised by this approach. We have performed an error analysis of the output of our classifier, with a view to casting light both on the systems performance, and on the da classification scheme itself.

YPA — an Intelligent Directory Enquiry Assistant

The YPA project is building a system to make the information in classified directories more accessible. BTs Yellow Pages®1 provides an example of classified database with which this work would be useful.There are two reasons for doing this: (i) directories like Yellow Pages contain much useful but hard-to-access information, especially in the free text in semi-display advertisements; (ii) more generally, the project is a demonstrator for exploitation of semi-structured data — data that is less systematic than database entries or logical clauses, but more systematic than free text because it has been marked up, for display or some other purpose.Accessing the directory source data file requires both natural language processing (for softening the interface to the system, and separately for analysis of natural-language-like constructs in the data) and information retrieval techniques, which are assisted by shallow knowledge. Deep world knowledge is impractical.The project seeks to get maximum effect from conveniently simplified approximations of standard natural language processing and knowledge representation. The paper gives an overview of the system, and illustrates its style with points about how the source data file is analysed. The YPA requires further development, but already demonstrates the effectiveness of shallow processing applied to semi-structured data.

Deliberative E-Rulemaking Project: Challenges to Enacting Real World Deliberation

ABSTRACT This article describes the challenges facing a federal government–funded initiative to promote online deliberation to improve the public comment process by federal and state government agencies in the United States. The three year project met several difficulties. Some have been technical, but our primary obstacle has been in securing partnerships with government agencies. Due to institutional, legal, and organizational challenges, many government agencies are resistant to opening up the public comment process to a deliberative structure, although some change occurred following the Obama administrations Open Government Initiative. This article describes the objectives of the original research project and details the challenges faced with the hope of guiding future deliberation research projects that aim to work with federal agencies in the U.S.

Public policy and obstacles to the virtual agora: insights from the deliberative e-rulemaking project

Cyber-optimists anticipate that electronic media will serve as an extensive public space, a virtual agora, that will re-engage the public with politics and the policies that affect everyday life. For three years we were involved in a U.S. National Science Foundation funded project designed to enhance the participation of citizens in government agency rulemaking processes using online public deliberation and Natural Language Processing technologies. Despite a promising approach in an important arena for direct and regular public engagement, the project was met with serious obstacles in trying to secure a partnership with a government agency or interest groups. This led us to consider the policy process literature for insights regarding the obstacles we faced. That literature, a mainstay in the public policy and public administration curriculum in the U.S. and an attempt to capture how policy makers actually make decisions, heavily focuses on institutional actors and their adversarial relationships. Yet, it provides for hardly any role for the public to participate in what ideally should be a democratic process. Important components of the literature imply that institutional actors should discourage direct public engagement. The analysis seeks to clarify leverage points and contexts that could be used to promote online public engagement as a regular component of government processes.

Special issue on interactive question answering: introduction

In this introduction, we present our overview of interactive question answering (IQA). We contextualize IQA in the wider field of question answering, and establish connections to research in Information Retrieval and Dialogue Systems. We highlight the development of QA as a field, and identify challenges in the present research paradigm for which IQA is a potential solution. Finally, we present an overview of papers in this special issue, drawing connections between these and the challenges they address.

The AMITIÉS system : Data-driven techniques for automated dialogue

We present a natural-language customer service application for a telephone banking call center, developed as part of the AMITIES dialogue project (Automated Multilingual Interaction with Information and Services). Our dialogue system, based on empirical data gathered from real call-center conversations, features data-driven techniques that allow for spoken language understanding despite speech recognition errors, as well as mixed system/customer initiative and spontaneous conversation. These techniques include robust named-entity extraction, slot-filling Frame Agents, vector-based task identification and dialogue act classification, a Bayesian database record selection algorithm, and a natural language generator designed with templates created from real agents expressions. Preliminary evaluation results indicate efficient dialogues and high user satisfaction, with performance comparable to or better than that of current conversational information systems.