Information Structure in Discourse

Institute for Communicating and Collaborative SystemsThe present dissertation proposes integrating Discourse Representation Theory (DRT), information structure (IS) and Combinatory Categorial Grammar (CCG) into a single framework. It achieves this by making two new contributions to computational treatment of information structure. First, it presents an uncomplicated approach to incorporating information structure in DRT. Second, it shows how the new DRT representation can be integrated into a unification-based grammar framework in a straightforward manner. We foresee the main application of the new formalism to be in spoken language systems: the approach presented here has the potential to considerably facilitate spoken language systems benefiting from insights derived from information structure. The DRT representation with information structure which is proposed in this dissertation is simpler than the previous attempts to include information structure in DRT. We believe that the simplicity of the Information-Structure-marked Discourse Representation Structure (IS-DRS) is precisely what makes it attractive and easy to use for practical tasks like determining the intonation in spoken language applications. The IS component in ISDRS covers a range of aspects of information structural semantics. A further advantage of IS-DRS is that in its case a single semantic representation is suitable for both the generation of context-appropriate prosody and automatic reasoning. A semantic representation on its own is useful for describing and analysing a language. However, it is of even greater utility if it is accompanied by a mechanism that allows one to directly infer the semantic representation from a natural language expression. We incorporated the IS-DRS into the Categorial Grammar (CG) framework, developing a unification based realisation of Combinatory Categorial Grammar, which we call Unification-based Combinatory Categorial Grammar (UCCG). UCCG inherits elements from Combinatory Categorial Grammar and Unification Categorial Grammar. The UCCG framework is developed gradually throughout the dissertation. The information structural component is included as the final step. The IS-DRSs for linguistic expressions are built up compositionally from the IS-DRSs of their sub-expressions. Feature unification is the driving force in this process. The formalism is illustrated by numerous examples which are characterised by different levels of syntactic complexity and diverse information structure. We believe that the main assets of both the IS-DRSs as well as the Unification-based Combinatory Categorial Grammar framework are their simplicity, transparency, and inherent suitability for computational implementation. This makes them an appealing choice for use in practical applications like spoken language systems

Individual and Domain Adaptation in Sentence Planning for Dialogue

One of the biggest challenges in the development and deployment of spoken dialogue systems is the design of the spoken language generation module. This challenge arises from the need for the generator to adapt to many features of the dialogue domain, user population, and dialogue context. A promising approach is trainable generation, which uses general-purpose linguistic knowledge that is automatically adapted to the features of interest, such as the application domain, individual user, or user group. In this paper we present and evaluate a trainable sentence planner for providing restaurant information in the MATCH dialogue system. We show that trainable sentence planning can produce complex information presentations whose quality is comparable to the output of a template-based generator tuned to this domain. We also show that our method easily supports adapting the sentence planner to individuals, and that the individualized sentence planners generally perform better than models trained and tested on a population of individuals. Previous work has documented and utilized individual preferences for content selection, but to our knowledge, these results provide the first demonstration of individual preferences for sentence planning operations, affecting the content order, discourse structure and sentence structure of system responses. Finally, we evaluate the contribution of different feature sets, and show that, in our application, n-gram features often do as well as features based on higher-level linguistic representations

Access to recorded interviews: A research agenda

Recorded interviews form a rich basis for scholarly inquiry. Examples include oral histories, community memory projects, and interviews conducted for broadcast media. Emerging technologies offer the potential to radically transform the way in which recorded interviews are made accessible, but this vision will demand substantial investments from a broad range of research communities. This article reviews the present state of practice for making recorded interviews available and the state-of-the-art for key component technologies. A large number of important research issues are identified, and from that set of issues, a coherent research agenda is proposed

Description of the Chinese-to-Spanish rule-based machine translation system developed with a hybrid combination of human annotation and statistical techniques

Two of the most popular Machine Translation (MT) paradigms are rule based (RBMT) and corpus based, which include the statistical systems (SMT). When scarce parallel corpus is available, RBMT becomes particularly attractive. This is the case of the Chinese--Spanish language pair. This article presents the first RBMT system for Chinese to Spanish. We describe a hybrid method for constructing this system taking advantage of available resources such as parallel corpora that are used to extract dictionaries and lexical and structural transfer rules. The final system is freely available online and open source. Although performance lags behind standard SMT systems for an in-domain test set, the results show that the RBMT’s coverage is competitive and it outperforms the SMT system in an out-of-domain test set. This RBMT system is available to the general public, it can be further enhanced, and it opens up the possibility of creating future hybrid MT systems.Peer ReviewedPostprint (author's final draft

Towards a Unified Knowledge-Based Approach to Modality Choice

This paper advances a unified knowledge-based approach to the process of choosing the most appropriate modality or combination of modalities in multimodal output generation. We propose a Modality Ontology (MO) that models the knowledge needed to support the two most fundamental processes determining modality choice – modality allocation (choosing the modality or set of modalities that can best support a particular type of information) and modality combination (selecting an optimal final combination of modalities). In the proposed ontology we model the main levels which collectively determine the characteristics of each modality and the specific relationships between different modalities that are important for multi-modal meaning making. This ontology aims to support the automatic selection of modalities and combinations of modalities that are suitable to convey the meaning of the intended message

Parsing of Spoken Language under Time Constraints

Spoken language applications in natural dialogue settings place serious requirements on the choice of processing architecture. Especially under adverse phonetic and acoustic conditions parsing procedures have to be developed which do not only analyse the incoming speech in a time-synchroneous and incremental manner, but which are able to schedule their resources according to the varying conditions of the recognition process. Depending on the actual degree of local ambiguity the parser has to select among the available constraints in order to narrow down the search space with as little effort as possible. A parsing approach based on constraint satisfaction techniques is discussed. It provides important characteristics of the desired real-time behaviour and attempts to mimic some of the attention focussing capabilities of the human speech comprehension mechanism.Comment: 19 pages, LaTe

Modelling Users, Intentions, and Structure in Spoken Dialog

We outline how utterances in dialogs can be interpreted using a partial first order logic. We exploit the capability of this logic to talk about the truth status of formulae to define a notion of coherence between utterances and explain how this coherence relation can serve for the construction of AND/OR trees that represent the segmentation of the dialog. In a BDI model we formalize basic assumptions about dialog and cooperative behaviour of participants. These assumptions provide a basis for inferring speech acts from coherence relations between utterances and attitudes of dialog participants. Speech acts prove to be useful for determining dialog segments defined on the notion of completing expectations of dialog participants. Finally, we sketch how explicit segmentation signalled by cue phrases and performatives is covered by our dialog model.Comment: 17 page

Estudios acerca del establecimiento de conexiones entre enunciados hablados: ¿qué pueden contribuir a la promoción de la construcción de una representación coherente del discurso por parte de los estudiantes?

The aim of this article is to provide an overview of how the establishment of discourse connections among spoken statements has been studied by approaches to discourse analysis and psycholinguistic studies, in order to highlight what variables appear to be important for understanding how comprehension of spoken discourse can be facilitated. The consideration of discourse analysis approaches allows us to think about the role of the establishment of discourse connections among speech acts in the classroom, the uses of contextualization cues by bilingual students, the identification of social and cultural notions in teachers’ discourse, and the interactional effects of teachers’ interventions. Preliminary psycholinguistic studies contribute to our understanding of the role of establishing causal connections and integrating adjacent statements through the presence of discourse markers in the comprehension of spoken discourse by college students. The results of these approaches and studies provide insight into students’ comprehension of classroom discourse, and hold the potential for implications for instruction.El propósito de este artículo es realizar un recorrido a través de enfoques de análisis del discurso y estudios de psicolingüística que han investigado el establecimiento de conexiones entre enunciados hablados, a fin de destacar las variables que parecen ser centrales para facilitar la comprensión. La consideración de los enfoques del análisis del discurso nos permitirán pensar acerca del rol del establecimiento de conexiones entre actos del lenguaje en el aula, las funciones de las claves de contextualización, la identificación de las nociones sociales y culturales en el discurso de los profesores, los efectos de las intervenciones de los profesores en la interacción con los estudiantes. Los estudios preliminares de psicolingüística contribuirán a nuestra comprensión del rol del establecimiento de conexiones causales e integración de enunciados adyacentes a través de marcadores del discurso por parte de estudiantes universitarios. La consideración de estos enfoques y estudios nos ayudarán a pensar acerca de las contribuciones que sus propuestas y métodos pueden hacer al enriquecimiento de nuestro entendimiento de cómo los estudiantes comprenden el discurso producido durante las clases.Fil: Yomha Cevasco, Jazmin. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Broek, Paul van den. Leiden University; Países Bajo