The acceptance of natural language generation systems strongly depends on their capability to facilitate the exchange of information with human users. Current generation systems consider the influence of situational factors on the content and the form of the resulting utterances. However, the need to time their processing flexibly is usually neglected although temporal factors play a central part when directly addressing a human communication partner. A short response time of a system is crucial for its effective use. Furthermore, some applications --- e.g., the simultaneous description of ongoing events --- even necessitate the interleaving of input consumption and output production, i.e. the use of an incremental processing mode. We claim that incremental processing is a central design principle for developing flexible and efficient generators for speech output. We discuss the advantages of parallel processing for incremental generation and several aspects of control of the generator...

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In this mlicle, we 1)reseu! a statistical approach to machine translatiou that is based on Data-Oriented Parsing: l)ata-Oriented Translatiou (DOT). In DOT, we use liuked subtree pairs for creating a derivation of a source seutencc. Each linked subtree lmir has a certain probability, and cousists of two trees: one in the source language and oue in the target lan~ gnage. When a dcriwtfion has been formed with these subtree pairs, we can create a lrauslation fi'om this deriwltion. Since there are typically mauy dif- ferent dcrivatious of lhe same sentence in the source language, there can be a, many different translations for it. The probability of a translatiou can be calculated as the total probability of fill the derivations that form this translatiou. We give the computatioual aspects for tiffs model, show that we can convcrt each subtree pair into a productive rewrite rule, and that the most probable translatiou can be computed by means of Monte Carlo disambiguation. Finally, we discuss some pilot experimeuts with the Veal)mobil corpus.

In this paper we present one aspect of our presents a clear case of where general as well as specific research on machine translation (MT): defining the re- real world knowledge should assist in eliminating inap- lation between the interlingua (IL) and a knowledge representation (KR) within an MT system. Our interest lies in the translation of natural language (NL) sentences where the "message" contains a spatial relation in particular, where the sentence conveys information about the location or path of physical entities in the real, physical world. We explore several arguments for clarifying the source of constraints on the particular IL structures needed to translate these sentences.

Abstract. This paper describes an approach for handling structural divergences and recovering dropped arguments in an implemented Korean to English machine translation system. The approach relies on canonical predicate-argument structures (or dependency structures), whichprovide a suitable pivot representation for the handling of structural divergences and the recovery of dropped arguments. It can also be converted to and from the interface representations of many o-the-shelf parsers and generators. 1

In synchronous rewriting, the productions of two rewriting systems are paired and applied synchronously in the derivation of a pair of strings. We present a new synchronous rewriting system and argue that it can handle certain phenomena that are not covered by existing synchronous systems.

This paper proposes the use of "pattern-based" context-free grammars as a basis for building machine translation (MT) systems, which are now being adopted as personal tools by a broad range of users in the cyberspace society. We discuss major requirements for such tools, including easy customization for diverse domains, the efficiency of the translation algorithm, and scalability (incremental improvement in translation quality through user interaction), and describe how our approach meets these requirements.

A dissertation submitted in fulfilment of the requirements for the award of

This paper is a survey of the current machine translation research in the US, Europe and Japan. A short history of machine translation is presented first, followed by an overview of the current research work. Representative examples of a wide range of different approaches adopted by machine translation researchers are presented. These are described in detail along with a discussion of the practicalities of scaling up these approaches for operational environments. In support of this discussion, issues in, and techniques for, evaluating machine translation systems are addressed.

this paper is to highlight a area of MT usually ignored, and to propose a non-theory specific solution, we will not give an overview of all types of MT systems.