This special issue brings together representative views on what has come to be known as "best practice" in the development and evaluation of spoken language dialogue systems (SLDSs). The issue was initiated in the context of the European Esprit project DISC, which ran from June 1997 till February 2000. DISC's main goal was to identify current practice in both the development and the evaluation of SLDSs, in order to arrive at a useful definition and description of best practice. The project has resulted in a collection of guidelines which are intended for different target groups, in particular developers, deployers and customers.DISC partners were: Natural Interactive Systems Laboratory, Odense University, Denmark (coordination); Department of Speech, Music and Hearing (KTH), Stockholm, Sweden; Human-Machine Communication Department, CNRS-LIMSI, Orsay, France; Institute for Natural Language Processing (IMS), University of Stuttgart, Germany; Vocalis Ltd, Cambridge, United Kingdom; DaimlerChrysler Research Center Ulm, Germany; and the ELSNET foundation, Utrecht, The Netherlands.

The last few years the interest in SLDSs has increased enormously. At present there is a large number of systems available, many of them for commercial use. Their number is growing rapidly, and so are the variety of their functionalities and the diversity of their application domains. The tasks that advanced systems are able to perform are often more complex, less stereotypical, and are often carried out in the context of several interconnected domains of application. With these advances have come higher expectations of the naturalness and intelligence with which SLDSs fulfill their assignments, and as a consequence the interest in such systems has even grown more, both within academic and commercial circles. As far as natural human- system interaction is concerned, one significant change in SLDS design concerns the interaction between natural language understanding and dialogue management. Here we see a clear tendency towards models that incorporate a substantial amount of discourse semantics and make use of some conception of context-change. This allows for more natural interactions between the system and its human users, due on the one hand to the system's improved ability to compute the intended meaning of the user's input and on the other to the increased sophistication of the strategies it uses for planning its own responses. Such improved capacities are crucial when the system is to leave more of the initiative to the user, instead of keeping the dialogue on a narrowly circumscribed path of largely predictable exchanges. Further, there is a tendency to combine spoken language human-system interaction with other modalities of information exchange and representation (e.g., images and gestures), asking for both modality-specific and modality-integrating syntactic and semantic processing capabilities. All these developments have led to a situation in which there is a great need, shared by developers, deployers and customers alike, for effective guidelines, which will enable them to make accurate and successful design and implementation decisions, in accordance with broad consensus of what must be best practice in this particular engineering domain.

In this paper, we present a novel approach to partial parsing that produces dependency links between words of a sentence. The partial parser called a lightweight dependency analyzer uses information encoded in supertags and hence can produce constituency-based as well as dependency-based analyses. The lightweight dependency analyzer has been used for text chunking, including noun and verb group chunking. We also present a proposal for a general framework for parser evaluation that is applicable for evaluating both constituency-based and dependency-based, partial and complete parsers. The performance results of the lightweight dependency analyzer on Wall Street Journal and Brown corpus using the proposed evaluation metrics are discussed.

This issue of Natural Language Engineering journal reports on recent achievements in the domain of HPSG-based parsing. Research groups at Saarbrücken, CSLI Stanford and the University of Tokyo have worked on grammar development and processing systems that allow the use of HPSG-based processing in practical application contexts. Much of the research reported here has been collaborative, and all of the work shares a commitment to producing comparable results on wide-coverage grammars with substantial test suites. The focus of this special issue is deliberately narrow, to allow detailed technical reports on the results obtained among the collaborating groups. Thus, the volume cannot aim at providing a complete survey on the current state of the field. This introduction summarizes the research background for the work reported in the issue, and puts the major new approaches and results into perspective. Relationships to similar efforts pursued elsewhere are included, along with a brief summary of the research and development efforts reflected in the volume, the joint reference grammar, and the common sets of reference data.

This paper describes our work on dialogue systems that can mimic human conversation, with the goal of providing intuitive access to a wide range of applications by expanding the user's options in the interaction. We concentrate on practical dialogue: dialogues in which the participants need to accomplish some objective or perform some task. Two hypotheses regarding practical dialogue motivate our research. First, that the conversational competence required for practical dialogues, while still complex, is significantly simpler to achieve than general human conversational competence. And second, that within the genre of practical dialogue, the bulk of the complexity in the language interpretation and dialogue management is independent of the task being performed. If these hypotheses are true, then it should be possible to build a generic dialogue shell for practical dialogue, by which we mean the full range of components required in a dialogue system, including speech recognition, language processing, dialogue management and response planning, built in such a way as to be readily adapted to new applications by specifying the domain and task models. This paper documents our progress and what we have learned so far based on building and adapting systems in a series of different problem solving domains.

Modern grammar development platforms often support multiple devices for representing properties of a natural language, giving the grammar writer some freedom in implementing analyses of linguistic phenomena. These design alternatives can have dramatic consequences for efficiency both in processing and in grammar building. In this paper I report on three experiments in making systematic modifications to a broad-coverage grammar of English in order to gain efficiency without loss of linguistic elegance. While the experiments are to some degree both platform-dependant and theory-bound, the kinds of modifications reported should be applicable to any unification-based grammar which makes use of types. The results make a strong case for a more visible role for the linguist in the collaborative effort to achieve greater processing efficiency.

An algorithmic approach to the semantic interpretation of deverbal nominalizations found in encyclopedic texts, such as support, publication and control, is described. Interpreting these nominalizations is crucial because they are quite common in encyclopedic texts, hence a great deal of information is represented within them. Interpretation involves three tasks: deciding whether the nominalization is being used in a verbal or non-verbal sense; disambiguating the nominalized verb when a verbal sense is used; and determining the fillers of the thematic roles of the verbal concept or predicate of the nominalization. A verbal sense can be recognized by the presence of modifiers that represent the arguments of the verbal concept. It is these same modifiers which provide the semantic clues to disambiguate the nominalized verb. In the absence of explicit modifiers, heuristics are used to discriminate between verbal and non-verbal senses. A correspondence between verbs and their nominalizations is exploited so that only a small amount of additional knowledge is needed to handle the nominal form. These methods are tested in the domain of encyclopedic texts and the results are shown.

One major obstacle to the efficient processing of large wide coverage grammars in unification-based grammatical frameworks such as HPSG is the time and space cost of the unification operation itself. In a grammar development system it is not appropriate to address this problem with techniques which involve lengthy compilation, since this slows down the edit-test-debug cycle. Nor is it possible to radically restructure the grammar. In this paper, we describe novel extensions to an existing efficient unification algorithm which improve its space and time behaviour (without affecting its correctness) by substantially increasing the amount of structure sharing that takes place. We also describe a fast and automatically tunable pre-unification filter (the ‘quick check’) which in practice detects a large proportion of unifications that if performed would fail. Finally, we present an efficient algorithm for checking for subsumption relationships between two feature structures; a special case of this gives a fast equality test. The subsumption check is used in a parser (described elsewhere in this issue) which ‘packs’ local ambiguities to avoid performing redundant sub-computations.

This paper is a case study of user involvement in the requirements specification for project ISLE: Interactive Spoken Language Education. Developers of Spoken Language Dialogue Systems should involve users from the outset, particularly if the aim is to develop novel solutions for a generic target application area or market. As well as target end-users, SLDS developers should identify and consult ‘meta-level’ domain experts with expertise in human-to-human dialogue in the target domain. In our case, English language teachers and publishers provided generic knowledge of learners' dialogue preferences; other applications have analogous domain language experts. These domain language experts can help to pin down a domain-specific sublanguage which fits the constraints of current speech recognition technology: linguistically-naive end-users may expect unconstrained conversational English, but in practice, dialogue interactions have to be constrained in vocabulary and syntax. User consultation also highlighted a need to consider how to integrate speech input and output with other modes of interaction and processing; in our case the input speech signal is processed by speech recogniser, stress and mispronunciation detectors, and output responses are text and graphics as well as speech. This suggests a need to revisit the definition of ‘dialogue’: other SLDS developers should also consider the merits of multimodality as an adjunct to pure spoken language dialogue, particularly given that current systems are not capable of accurately handling unconstrained English.

In this paper, we propose a new ambiguity representation scheme; Structure Preference Relation (SPR), which consists of useful quantitative distribution information for ambiguous structures. Two automatic acquisition algorithms, the first acquired from a treebank, and the second acquired from raw texts, are introduced, and some experimental results which prove the availability of the algorithms are also given. Finally, we introduce some SPR applications in linguistics and natural language processing, such as preference-based parsing and the discovery of representative ambiguous structures, and propose some future research directions.

Prepositional Phrases (PP) perform a variety of syntactic functions in a conventional sentence, and cause severe problems to computer systems that automatically analyse the sentential syntax. A major issue in this area has been the automatic determination of the syntactic functions of PPs. Most work published so far makes use of the probabilistic approach, and attach PPs to either the antecedent noun or verb phrase. Due to the natural limitation of the probabilistic approach, it is important to evaluate the linguistic behaviour of prepositional phrases and propose qualitative solutions to the problem. In this article, I first provide a detailed account of statistics regarding the frequency of use for (i) types of prepositions, (ii) syntactic categories as realisations of prepositional complements, and (iii) the syntactic functions of prepositional phrases. Statistics reported here all derive from a representative corpus of contemporary British English. I then describe a set of rules that has been implemented in order to label PPs automatically for their syntactic functions. I finally report on the coverage of these rules empirically observed in an experiment which involved a set of naturally occurring PPs as test data.

Whilst Spoken Language Dialogue Systems (SLDSs) technology has made good progress in recent years, the issue of SLDS usability is still lagging behind both theoretically and in actual SLDS development and evaluation. However, as more products reach the market and competition intensifies, there is growing recognition of the importance of systematically understanding the factors which must be taken into account in order to optimise SLDS usability. Ideally, this understanding should be comprehensive (i.e. include all major human factors perspectives on SLDSs), and exhaustive (i.e. describe each perspective as it pertains to the detailed development and evaluation of any possible SLDS). This paper addresses the requirement of comprehensiveness by decomposing the complex space of SLDS usability best practice into eleven issues which should be considered by developers during specification, design, development and evaluation. The discussion of each issue is aimed to support the developer in building SLDSs which are likely to generate user satisfaction, which are perceived to be easy to understand and control, and which enable smooth user- system interaction. Based on the best practice issues discussed, criteria for evaluating SLDS usability are proposed. Several limits to our current understanding of SLDS usability are highlighted.

This article evaluates the efficiency of the LiLFeS abstract machine by performing parsing tasks with the LinGO English resource grammar. The instruction set of the abstract machine is optimized for efficient processing of definite clause programs and typed feature structures. LiLFeS also supports various tools required for efficient parsing (e.g. efficient copying, a built-in CFG parser) and the constructions of standard Prolog (e.g. cut, assertions, negation as failure). Several parsers and large-scale grammars, including the LinGO grammar, have been implemented in or ported to LiLFeS. Precise empirical results with the LinGO grammar are provided to allow comparison with other systems. The experimental results demonstrate the efficiency of the LiLFeS abstract machine.

This article presents an HPSG parser using a technique called CFG filtering. The parser predicts possible parse trees using a CFG generated automatically from a given HPSG-based grammar. Parsing costs are reduced because unification is applied only to the predicted parse trees. In other words, parsing is speeded up because the parser avoids unnecessary unification by eliminating impossible parse trees. We show the method for generating a CFG from an HPSG-based grammar and outline a parsing scheme using the CFG. The effectiveness of the parsing scheme is shown through experimental results obtained by using several HPSG-based grammars, including the LinGO grammar.

In this paper, the August spoken dialogue system is described. This experimental Swedish dialogue system, which featured an animated talking agent, was exposed to the general public during a trial period of six months. The construction of the system was partly motivated by the need to collect genuine speech data from people with little or no previous experience of spoken dialogue systems. A corpus of more than 10,000 utterances of spontaneous computer- directed speech was collected and empirical linguistic analyses were carried out. Acoustical, lexical and syntactical aspects of this data were examined. In particular, user behavior and user adaptation during error resolution were emphasized. Repetitive sequences in the database were analyzed in detail. Results suggest that computer-directed speech during error resolution is increased in duration, hyperarticulated and contains inserted pauses. Design decisions which may have influenced how the users behaved when they interacted with August are discussed and implications for the development of future systems are outlined.

Applications of speech recognition are now widespread, but user-centred evaluation methods are necessary to ensure their success. Objective evaluation techniques are fairly well established, but previous subjective techniques have been unstructured and unproven. This paper reports on the first stage in the development of a questionnaire measure for the Subjective Assessment of Speech System Interfaces (SASSI). The aim of the research programme is to produce a valid, reliable and sensitive measure of users' subjective experiences with speech recognition systems. Such a technique could make an important contribution to theory and practice in the design and evaluation of speech recognition systems according to best human factors practice. A prototype questionnaire was designed, based on established measures for evaluating the usability of other kinds of user interface, and on a review of the research literature into speech system design. This consisted of 50 statements with which respondents rated their level of agreement. The questionnaire was given to users of four different speech applications, and Exploratory Factor Analysis of 214 completed questionnaires was conducted. This suggested the presence of six main factors in users' perceptions of speech systems: System Response Accuracy, Likeability, Cognitive Demand, Annoyance, Habitability and Speed. The six factors have face validity, and a reasonable level of statistical reliability. The findings form a useful theoretical and practical basis for the subjective evaluation of any speech recognition interface. However, further work is recommended, to establish the validity and sensitivity of the approach, before a final tool can be produced which warrants general use.

We describe and argue for a strategy of performance profiling and comparison in the engineering of parsing systems for wide-coverage linguistic grammars. A performance profile is a precise, rich and structured snapshot of system (and grammar) behaviour at a given development point. The aim is to characterize system performance at a very detailed technical level, but at the same time to abstract away from idiosyncracies of particular processors. Profiles are obtained with minimal effort by applying a specialized profiling tool to a set of structured reference data (taken from both existing test suites and corpora), in conjunction with a uniform format for test data and processing results. The resulting profiles can be analyzed and visualized at various levels of granularity in order to highlight different aspects of system performance, thus providing a solid empirical basis for system refinement and optimization. Since profiles are stored in a database, comparison with earlier versions, different parameter settings, or other processing systems is straightforward. We apply several salient performance metrics in a contrastive discussion of various (one-pass, bottom-up, chart-based) parsing strategies (viz. passive vs. active and uni- vs. bidirectional approaches). Based on insights gained from detailed performance profiles, we outline and evaluate a novel ‘hyper-active’ parsing strategy. We also present preliminary profiles for techniques for ‘packing’ of local ambiguities with respect to (partial) subsumption of feature structures.

The PET platform for experimentation with hpsg processing and implementation techniques is introduced. PET provides an extendible set of building blocks for the implementation of efficient processors. This enables straightforward comparison of different approaches, rapid development of new techniques and easy synthesis of known techniques. An overview of the basic design is given and key aspects of the implementation are discussed. Early empirical results on the three standard test sets for the LinGO grammar are given. Two improved expansion strategies are evaluated empirically. The results of fine tuning the quick check filtering method through empirical study are discussed as an exemplar of the proposed experimental approach to the development and optimization of processing techniques. An overview of the progress in processing the LinGO grammar made over a development period of three years is given.

This article provides a global overview of the main aspects of current practice in the design, implementation and evaluation of speech recognition components for Spoken Language Dialog Systems (SLDSs), and presents the results of the DISC European project related to speech recognition. DISC and its successor DISC-2 are efforts towards the definition of best practice guidelines for SLDS development and evaluation. SLDSs aim at using natural spoken input for performing an information processing task such as automated standards, call routing or travel planning and reservations. The main functionality of an SLDS are speech recognition, natural language understanding, dialog management, database access and interpretation, response generation and speech synthesis. Speech recognition, which transforms the acoustic signal into a string of words, is a key technology in any SLDS.

The LinGO grammar consists of a specification of a type system and of various typed feature structures which are well-formed according to the type system. The typed feature structures function as grammar rules, lexical rules and lexical entries. There are several variant typed feature structure formalisms, with different computational properties, so in this appendix we very briefly specify the version assumed by the LinGO grammar.

This appendix is necessarily terse, and is only intended to allow a reader who already has a knowledge of typed feature structures to understand the specific formalism used in the LinGO grammar. The definitions given below basically follow Carpenter (1992), with the notion of type constraint from Copestake (1992). For formal details of typed feature structures in general see Carpenter (1992). A detailed account of the specific assumptions made here is given in Copestake (1999) (See Chapter 4 for an introduction, and Chapter 5 for a semi-formal account.)

Note that the LinGO grammar uses a very restricted formalism. For instance, it does not utilize disjunctive feature structures, negation, implication, inequalities, defaults, set-valued features, extensionality or relational constraints. Constraint resolution does not require that every type be made maximally specific, and the type inference system is essentially non-recursive. The recursive power necessary in grammars is explicitly encoded via rules, which are expressed as typed feature structures, but interpreted as phrase structure rules.