Robust Grammatical Analysis for Spoken Dialogue Systems

We argue that grammatical analysis is a viable alternative to concept spotting for processing spoken input in a practical spoken dialogue system. We discuss the structure of the grammar, and a model for robust parsing which combines linguistic sources of information and statistical sources of information. We discuss test results suggesting that grammatical processing allows fast and accurate processing of spoken input.Comment: Accepted for JNL

Type-driven semantic interpretation and feature dependencies in R-LFG

Once one has enriched LFG's formal machinery with the linear logic mechanisms needed for semantic interpretation as proposed by Dalrymple et. al., it is natural to ask whether these make any existing components of LFG redundant. As Dalrymple and her colleagues note, LFG's f-structure completeness and coherence constraints fall out as a by-product of the linear logic machinery they propose for semantic interpretation, thus making those f-structure mechanisms redundant. Given that linear logic machinery or something like it is independently needed for semantic interpretation, it seems reasonable to explore the extent to which it is capable of handling feature structure constraints as well. R-LFG represents the extreme position that all linguistically required feature structure dependencies can be captured by the resource-accounting machinery of a linear or similiar logic independently needed for semantic interpretation, making LFG's unification machinery redundant. The goal is to show that LFG linguistic analyses can be expressed as clearly and perspicuously using the smaller set of mechanisms of R-LFG as they can using the much larger set of unification-based mechanisms in LFG: if this is the case then we will have shown that positing these extra f-structure mechanisms is not linguistically warranted.Comment: 30 pages, to appear in the the ``Glue Language'' volume edited by Dalrymple, uses tree-dvips, ipa, epic, eepic, fullnam

A Note on the Complexity of Restricted Attribute-Value Grammars

The recognition problem for attribute-value grammars (AVGs) was shown to be undecidable by Johnson in 1988. Therefore, the general form of AVGs is of no practical use. In this paper we study a very restricted form of AVG, for which the recognition problem is decidable (though still NP-complete), the R-AVG. We show that the R-AVG formalism captures all of the context free languages and more, and introduce a variation on the so-called `off-line parsability constraint', the `honest parsability constraint', which lets different types of R-AVG coincide precisely with well-known time complexity classes.Comment: 18 pages, also available by (1) anonymous ftp at ftp://ftp.fwi.uva.nl/pub/theory/illc/researchReports/CT-95-02.ps.gz ; (2) WWW from http://www.fwi.uva.nl/~mtrautwe

Concurrent Lexicalized Dependency Parsing: The ParseTalk Model

A grammar model for concurrent, object-oriented natural language parsing is introduced. Complete lexical distribution of grammatical knowledge is achieved building upon the head-oriented notions of valency and dependency, while inheritance mechanisms are used to capture lexical generalizations. The underlying concurrent computation model relies upon the actor paradigm. We consider message passing protocols for establishing dependency relations and ambiguity handling.Comment: 90kB, 7pages Postscrip

Mixing representation levels: The hybrid approach to automatic text generation

Natural language generation systems (NLG) map non-linguistic representations into strings of words through a number of steps using intermediate representations of various levels of abstraction. Template based systems, by contrast, tend to use only one representation level, i.e. fixed strings, which are combined, possibly in a sophisticated way, to generate the final text. In some circumstances, it may be profitable to combine NLG and template based techniques. The issue of combining generation techniques can be seen in more abstract terms as the issue of mixing levels of representation of different degrees of linguistic abstraction. This paper aims at defining a reference architecture for systems using mixed representations. We argue that mixed representations can be used without abandoning a linguistically grounded approach to language generation.Comment: 6 page

situ-f: a domain specific language and a first step towards the realization of situ framework

Situ proposes a human centered, dynamic reasoning framework for domain experts to evolve their software. It formally models the relationship between externally observed situation sequences and the rapid evolution of that software system, using real-time usage information from users and contextual capturing on the behavior of a software system relative to its runtime environment. Situf is a continuing effort under Situ framework. In this effort, a domain specific, functional programming language named Situf is presented from its design, semantics and a feasibility test through theoretical validation. The targeted users of this language mainly include domain experts and engineers who are versed in the major concepts and paradigms regarding human-centric situations. As argued there, human-centric situations are vitally important to infer a user\u27s intention and therefore, to drive software service evolution. Situf is designed particularly to encourage domain experts and engineers to think and work with situations. An attribute grammar based approach is developed so that through Situf , relevant real-time contexts can be systematically aggregated around situations. A computational semantics is offered to precisely describe the runtime behavior of a Situf program. While the Situf language serves as the critical centerpiece of this work, its functioning necessarily requires environmental support from Situ elements outside the language itself, such that altogether they give rise to a Situ oriented system. This environment, named Situf -based environment, is also introduced