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Automatically summarizing vast amounts of on-line quantitative data with a short natural language paragraph has a wide range of real-world applications. However, this specific task raises a number of difficult issues that are quite distinct from the generic task of language generation: conciseness, complex sentences, floating concepts, historical background, paraphrasing power and implicit content. In this thesis, I address these specific issues by proposing a new generation model in which a first pass builds a draft containing only the essential new facts to report and a second pass incrementally revises this draft to opportunistically add as many background facts as can fit within the space limit. This model requires a new type of linguistic knowledge: revision operations, which specifyies the various ways a draft can...

this paper is an attempt to resolve these problems in a satisfactory manner. Although we believe that this algorithm could be seen as an instance of a uniform architecture for parsing and generation--just as the extended Earley parser (Shieber, 1985b) and the bottom-up generator were instances of the generalized Earley deduction architecture---our efforts to date have been aimed foremost toward the development of the algorithm for generation alone. We will mention efforts toward this end in Section 5

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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this paper is that neither has been implemented." ([Vaughan and McDonald, 1986], page 95). Although Meteer [1990] gives a detail description of the relationship between text structure and revision it is unclear how the proposed model could contribute to the choice problem of paraphrases (see section 5.2). How- ever, from the approach described above and from the system described in [Meteer, 1990] we can draw the following conclusions. Only the generatoFs input is marked. If the generator encounters alternative realizations the revision component is asked to make the decision. However, to be able to do this it needs detailed knowledge about the grammar. Therefore grammatical knowledge has to be duplicated. The linguistic realization component used in [Meteer, 1990] is MUMBLE-86 [McDonald, 1986]. The text structural representation level must completely specify the infor- mation to be expressed by the utterance. The mapping has to ensure that all the necessary linguistic information is present. Mumblers procedural grammar is used only for generation purposes. Therefore it is without reach for the revision model to take into account relevant sources of ambiguities

Many existing natural language generation systems can be characterized according to their modularization as either pipelined or interleaved. In these separated systems, the generator is divided into several modules (e.g., planning and realization), with control and information passing between the modules during the generation process. This paper proposes a third type of generator, which we call integrated, that unifies the modules into a single mechanism. The mechanism uses a small set of orthogonal basic operations to produce planned and grammatical language output. Integrated systems are conceptually attractive and may support generation of pragmatic effects more effectively than other systems. After discussing the advantages of the integrated approach, we summarize GLINDA, an integrated generator currently under development at Carnegie Mellon. GLINDA is the generator used for narration and intercharacter communication in the Oz Interactive Fiction and Virtual Reality Project.

This paper 1 presents a new model for the produc tion of natural language. The novel idea is to com bine incremental and bidirectional generation with parallelism. The operational basis of our model is a distributed parallel system at every level of repre sentation. Starting point of the production are seg ments of the conceptual level. These segments are related to active objects which have to map them selves across the linguistic levels (i.e. functional-semantic, syntactic and morphologic level) as fast and as independently as possible. Therefore the in cremental behavior caused by a successive input is propagated on all levels. Linguistic requirements de tected by objects which are related to already pro duced segments at any level influence and restrict the decision of what to say next. 1

We present anew model of natural language processing in which natural language parsing and generation are strongly interleaved tasks. Interleaving of parsing and generation is important if we assume that natural language understanding and production are not only performed in isolation but also work together to obtain subsentential interactions in text revision or dialog systems. The core of the model is a new uniform agenda-driven tabular algorithm, called UTA. Although uniformly de ned, UTA is able to con gure itself dynamically for either parsing or generation, because it is fully driven by thestructure of the actual input|a string for parsing and a semantic expression for generation. Efficient interleaving of parsing and generation is obtained through item sharing between parsing and generation. This novel processing strategy facilitates the automatic exchange of items (i.e., partial results) computed in one direction to the other direction as well. The advantage of UTA in combination with the item sharing method is that we are able to extend the use of memorization techniques to the case of an interleaved approach. In order to demonstrate UTA's utility for developing high-level performance methods, we present a new algorithm for incremental self-monitoring during natural language production.

This paper describes the construction of syntactic structures within an incremental multi-level and parallel generation system. Incremental and parallel generation imposes special requirements upon syntactic descr:.ption and processing. A head-driven grammar represented in a unification-based formalism is introduced which satisfies these demands. Furthermore the basic mechanisms for the parallel processing of syntactic segments are presented.