CLARIE: the Clarication Engine (original) (raw)

CLARIE: Handling Clarification Requests in a Dialogue System

Research on Language and Computation, 2006

This paper sets out a approach to clarification requests (CRs) general enough to cover all the major forms found in corpus data and specific enough to analyse the questions they ask about individual words and phrases. Its main features are a view of utterances as contextual abstracts with a radically abstracted semantic representation, and a view of CRs as standard utterances asking standard questions, but showing a particular kind of contextual dependence. It shows how it can be implemented computationally within a prototype text-based dialogue system, CLARIE, allowing it not only to generate CRs to clarify unknown reference and learn new words, but also to interpret and respond to user CRs, with both capabilities integrated within the standard dialogue processes and governed by empirical evidence.

Processing Unknown Words in a Dialogue System

2002

This paper describes a method of processing unknown words in a HPSGbased dialogue system, with acquisition of lexical semantics via clarification questions answered by the user. Use of a highly contextualized semantic representation, together with an utterance-anaphoric view of clarification, allows the clarificational dialogue to be integrated within the grammar and governed by standard rules of conversation.

The Theory and Use of Clarification Requests in Dialogue

2004

Clarification requests are an important, relatively common and yet under-studied dialogue device allowing a user to ask about some feature (e.g. the meaning or form) of an utterance, or part thereof. They can take many different forms (often highly elliptical) and can have many different meanings (requesting various types of information). This thesis combines empirical, theoretical and implementational work to provide a study of the various types of clarification request that exist, give a theoretical analysis thereof, and show how the results can be applied to add useful capabilities to a prototype computational dialogue system.

Graph-based representations of clarification strategies supporting automatic dialogue management

Italian Journal of Computational Linguistics

This paper aims at presenting a dialogue-oriented approach to the construction of a graph knowledge base (KB) supporting task-oriented human-machine interactions. In particular, we focus on different pragmatic scenarios, facing the Common Ground issue and arguing that knowledge bases (in the form of graphs) are needed to make a clarification and recover pieces of information when inconsistencies occur during the communicative exchange. The main contributions of this work are: 1) a flexible dialog system architecture designed to be plugged into existing service infrastructures, 2) a graph-based knowledge representation protocol to manage both dialog domain and dialog management, 3) a detailed investigation of clarification requests forms with respect to their functions. After a brief introduction (see Section 1), we present: the theoretical underpinnings of the paper and the background work (see Section 2) our system architecture (see Sections 3 and 4) and the clarification requests (CRs) issue (see Section 5); our CRs classification, and some examples in context (see Section 6).

Software-Based Dialogue Systems: Survey, Taxonomy, and Challenges

ACM Computing Surveys

The use of natural language interfaces in the field of human-computer interaction (HCI) is undergoing intense study through dedicated scientific and industrial research. The latest contributions in the field, including deep learning approaches like recurrent neural networks (RNNs), the potential of context-aware strategies and user-centred design approaches, have brought back the attention of the community to software-based dialogue systems, generally known as conversational agents or chatbots. Nonetheless, and given the novelty of the field, a generic, context-independent overview of the current state of research on conversational agents covering all research perspectives involved is missing. Motivated by this context, this article reports a survey of the current state of research of conversational agents through a systematic literature review of secondary studies. The conducted research is designed to develop an exhaustive perspective through a clear presentation of the aggregated...

Pointing: A way toward explanation dialogue

1990

Abstract Explanation requires a dialogue. Users must be allowed to ask questions about previously given explanations. However, building an interface that allows users to ask follow-up questions poses a difficult challenge for natural language understanding because such questions often intermix meta-level references to the discourse with object-level references to the domain. We propose a hypertext-like interface that allows users to point to the portion of the system's explanation they would like clarified.

A method for development of dialogue managers for natural language interfaces

1993

This paper describes a method for the development of dialogue managers for natural language interfaces. A dialogue manager is presented designed on the basis of both a theoretical investigation of models for dialogue management and an analysis of empirical material. It is argued that for natural language interfaces many of the human interaction phenomena accounted for in, for instance, plan-based models of dialogue do not occur. Instead, for many applications, dialogue in natural language interfaces can be managed from information on the functional role of an utterance as conveyed in the linguistic structure. This is modelled in a dialogue grammar which controls the interaction. Focus structure is handled using dialogue objects recorded in a dialogue tree which can be accessed through a scoreboard by the various modules for interpretation, generation and background system access. A sublanguage approach is proposed. For each new application the Dialogue Manager is customized to meet the needs of the application. This requires empirical data which are collected through Wizard of Oz simulations. The corpus is used when updating the different knowledge sources involved in the natural language interface. In this paper the customization of the Dialogue Manager for database information retrieval applications is also described.

Experiences from combining dialogue system development with information extraction techniques

2004

Traditional Q&A systems are efficient at interpretation of single questions and extraction of the corresponding answer from unstructured texts, but cannot handle many of the interaction features that make dialogue systems so efficient for information access. Dialogue systems, on the other hand, can handle connected dialogues, but are normally developed to access structured data, often stored in databases. The challenge is therefore to combine these areas of language technology research and develop dialogue systems that can access information from unstructured text documents. A first step towards this goal is to use information extraction techniques that pull out relevant information from textual documents to compile unstructured information to a database. This might sound as a straightforward endeavour, but in practice, it involves a number of research issues, such as, handling different ontological perspectives, dealing with information gaps, inference both inside the dialogue and in the interpretation of source documents, etc. We have addressed this combined research issue of utilising information extraction techniques to automatically create structured databases from unstructured documents to be accessed by dialogue systems. A system, BirdQuest, has been developed based on a bird encyclopaedia from which information was extracted and transformed to a relational database. In the paper we present the system architecture, its components, and evaluations from the perspectives of users of the system and the development of a dialogue system that access a database created automatically utilising information extraction.

On the Means for Clarification in Dialogue

The ability to request clarification of utterances is a vital part of the communicative process. In this paper we discuss the range of possible forms for clarification requests, together with the range of readings they can convey. We present the results of corpus analysis which show a correlation between certain forms and possible readings, together with some indication of maximum likely distance between request and the utterance being clarified. We then explain the implications of these results for a possible HPSG analysis of clarification requests and for an ongoing implementation of a clarification-capable dialogue system. 1

Implementing clarification dialogues in open domain question answering

Natural Language Engineering, 2005

We examine the implementation of clarification dialogues, a mechanism for ensuring that question answering systems take into account user goals by allowing them to ask series of related questions either by refining or expanding on previous questions with follow-up questions, in the context of open domain Question Answering systems. We develop an algorithm for clarification dialogue recognition through the analysis of collected data on clarification dialogues and examine the importance of clarification dialogue recognition for question answering. The algorithm is evaluated and shown to successfully recognize the start and continuation of clarification dialogues in 94% of cases. We then show the usefulness of the algorithm by demonstrating how the recognition of clarification dialogues can simplify the task of answer retrieval.