A Robust and Efficient Three-Layered Dialogue Component for a Speech-to-Speech Translation System

We present the dialogue component of the speech-to-speech translation system VERBMOBIL. In contrast to conventional dialogue systems it mediates the dialogue while processing maximally 50% of the dialogue in depth. Special requirements like robustness and efficiency lead to a 3-layered hybrid architecture for the dialogue module, using statistics, an automaton and a planner. A dialogue memory is constructed incrementally.Comment: Postscript file, compressed and uuencoded, 15 pages, to appear in Proceedings of EACL-95, Dublin

Dialogue acts in automatic dialogue interpreting

In this paper we demonstrate that for an adequate translation of an utterance spoken in a dialogue the dialogue act it performs has to be determined. We introduce an approach that automatically assigns types of dialogue acts to utterances on the basis of both micro- and macro-structural information. Technically, this assignment is realized by modeling preference rules as weighted defaults in the Description Logic system FLEX. The dialogue-act type of an utterance is determined by qualitatively minimizing the exceptions to these defaults. The results described here have been developed within the VERBMOBIL project, a project concerned with face-to-face dialogue interpreting funded by the German Federal Ministry of Education, Science, Research and Technology (BMBF). We present the rather positive results of a first evaluation of this implementation showing the accuracy of dialogue act assignment

Språklig återkoppling i spontana dialoger

I denna uppsats undersöks språklig återkoppling i målstyrda spontana svenska talade dialoger. Syftet med studien var att undersöka förhållandet mellan språklig återkoppling och typen av angränsande talakt samt att studera prosodins roll för återkopplingens tolkning. Tre dialoger på sammanlagt ungefär 22 minuter analyserades. Språklig återkoppling definierades som en verbal interindividuell signal, som är en reaktion på en talares yttrande och som har ett visst syfte, från lyssnare till talaren i ett samtal utan att lyssnaren gör anspråk på turen

A Robust and Efficient Three-Layered Dialogue Component for a Speech-to-Speech Translation System

We present the dialogue component of the speech-to-speech translation system verbmobil. In contrast to conventional dialogue systems it mediates the dialogue while processing maximally 50% of the dialogue in depth. Special requirements (robustness and efficiency) lead to a 3-layered hybrid architecture for the dialogue module, using statistics, an automaton and a planner. A dialogue memory is constructed incrementally. 1 Introduction verbmobil combines the two key technologies speech processing and machine translation. The long-term goal of this project is the development of a prototype for the translation of spoken dialogues between two persons who want to find a date for a business meeting (for more detail on the objectives of verbmobil see [Wahlster, 1993]). A special characteristic of verbmobil This report also appears in the Proceedings of the EACL, Dublin, 1995. is that both participants are assumed to have at least a passive knowledge of English which is used as intermedia..

A robust and efficient three-layered dialogue component for a speech-to-speech translation system

We present the dialogue component of the speech-to-speech translation system VERBMOBIL. In contrast to conventional dialogue systems it mediates the dialogue while processing maximally 50% of the dialogue in depth. Special requirements (robustness and efficiency) lead to a 3-layered hybrid architecture for the dialogue module, using statistics, an automation and a planner. A dialogue memory is constructed incrementally. (orig.)Available from TIB Hannover: RR 5221(50)+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEBundesministerium fuer Forschung und Technologie (BMFT), Bonn (Germany)DEGerman

Quantifying mutual-understanding in dialogue

PhDThere are two components of communication that provide a natural index of mutual-understanding in dialogue. The first is Repair; the ways in which people detect and deal with problems with understanding. The second is Ellipsis/Anaphora; the use of expressions that depend directly on the accessibility of the local context for their interpretation. This thesis explores the use of these two phenomena in systematic comparative analyses of human-human dialogue under different task and media conditions. In order to do this it is necessary to a) develop reliable, valid protocols for coding the different Repair and Ellipsis/Anaphora phenomena b) establish their baseline patterns of distribution in conversation and c) model their basic statistical inter-relationships and their predictive value. Two new protocols for coding Repair and Ellipsis/Anaphora phenomena are presented and applied to two dialogue corpora, one of ordinary 'everyday' conversations and one of task-oriented dialogues. These data illustrate that there are significant differences in how understanding is created and negotiated across conditions. Repair is shown to be a ubiquitous feature in all dialogue. The goals of the speaker directly affect the type of Repair used. Giving instructions leads to a higher rate of self-editing; following instructions increases corrections and requests for clarification. Medium and familiarity also influence Repair; when eye contact is not possible there are a greater number of repeats and clarifications. Anaphora are used less frequently in task-oriented dialogue whereas types of Ellipsis increase. The use of Elliptical phrases that check, confirm or acknowledge is higher when there is no eye contact. Familiar pairs use more elliptical expressions, especially endophora and elliptical questions. Following instructions leads to greater use of elliptical (non-sentential) phrases. Medium, task and social norms all have a measureable effect on the components of dialogue that underpin mutual-understanding

Statistical language modelling of dialogue material in the British national corpus.

Statistical language modelling may not only be used to uncover the patterns which underlie the composition of utterances and texts, but also to build practical language processing technology. Contemporary language applications in automatic speech recognition, sentence interpretation and even machine translation exploit statistical models of language. Spoken dialogue systems, where a human user interacts with a machine via a speech interface in order to get information, make bookings, complaints, etc., are example of such systems which are now technologically feasible. The majority of statistical language modelling studies to date have concentrated on written text material (or read versions thereof). However, it is well-known that dialogue is significantly different from written text in its lexical content and sentence structure. Furthermore, there are expected to be significant logical, thematic and lexical connections between successive turns within a dialogue, but "turns" are not generally meaningful in written text. There is therefore a need for statistical language modeling studies to be performed on dialogue, particularly with a longer-term aim to using such models in human-machine dialogue interfaces. In this thesis, I describe the studies I have carried out on statistically modelling the dialogue material within the British National Corpus (BNC) - a very large corpus of modern British English compiled during the 1990s. This thesis presents a general introductory survey of the field of automatic speech recognition. This is followed by a general introduction to some standard techniques of statistical language modelling which will be employed later in the thesis. The structure of dialogue is discussed using some perspectives from linguistic theory, and reviews some previous approaches (not necessarily statistical) to modelling dialogue. Then a qualitative description is given of the BNC and the dialogue data within it, together with some descriptive statistics relating to it and results from constructing simple trigram language models for both dialogue and text data. The main part of the thesis describes experiments on the application of statistical language models based on word caches, word "trigger" pairs, and turn clustering to the dialogue data. Several different approaches are used for each type of model. An analysis of the strengths and weaknesses of these techniques is then presented. The results of the experiments lead to a better understanding of how statistical language modelling might be applied to dialogue for the benefit of future language technologies