AB S'll'RAC'I' in this paper we present a new dimension to paraphrasing text in which characteristics of the original text motivate strategies for effective pacaphrasing. Our system combines two existing robust components: the IRIJS-.II natural language underst~mding system and the SPOKESMAN generation system. We describe the architectur(: of the system and enhancements made to these components to facilitate paraphrasing. We particularly look at how levels of representation in these two systems are used by specialists in the paraphraser which define potential problems and paraphrasing strategies. Finally, we look at the role of paraphrasing in a cooperative dialog system. We will focus here on paraphrasing in the coutext of natural language interfaces and particularly on how multiple int::rpretations introduced by various kinds of ambiguity can be contrasted in paraphrases using both sentence structure and highlighting and folmating the text itself.
An improved version of IRACQ (for Interpretation Rule ACQuisition) is presented. I Our approach to semantic knowledge acquisition: 1) is in the context of a general purpose NL interface rather than one that accesses only databases, 2) employs a knowledge representation formalism with limited inferencing capabilities, 3) assumes a trained person but not an AI expert, and 4) provides a complete environment for not only acquiring semantic knowledge, but also maintaining and editing it in a consistent knowledge base. IRACQ is currently in use at the Naval Ocean Systems Center.
As part of DARPA's Strategic Computing Program, we have moved a large natural language system out of the laboratory. This involved: o Delivery of knowledge acquisition software to the Naval Ocean Systems Center (NOSC) to build linguistic knowledge bases, such as dictionary entries and case frames, o Demonstration of the natural language interface in a naval decision-making setting, and o Delivery of the interface software to Texas Instruments, which has integrated it into the total software package of the Strategic Computing Fleet Command Center Battle Management Program (FCCBMP). The resulting natural language interface will be delivered to the Pacific Fleet Command Center in Hawaii. This paper is an overview of this effort in technology transfer, indicating the technology features that have made this possible and reflecting upon what the experience illustrates regarding transportability, technology status, and delivery of natural language processing outside of a laboratory setting. The paper will be most valuable to those engaged in applying state-of-the-art techniques to deliver natural language interfaces and to those interested in developing the next generation of complete natural language interfaces. 1The work presented here was supported under DARPA contract ~NOOe14.-85-C-e616. The views and conclusions contained in this document ore those of the authors and should not be ~nterpreted as necessarily representing the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency or of the United States Government.
We evaluated large-vocabulary continuous-speech recognizer performance as a function of recognizer tuning parameters for 4 recognition task domains (location, date, time, yes/no) and two different applications (e.g. over-the-telephone reservations) that had some task domains in common. After defining a cost function that included false reject, false accept, and misrecognition errors, we determined optimum parameter values for each domain. The optimum parameter settings differed significantly across domains and even across applications for the same domain. Using a single set of parameter values for all of the tasks in an application can lead to substantial cost penalties for some individual tasks. These results suggest that there can be substantial benefit in using task-specific tuned recognition parameters. We describe a methodology and set of supporting tools for efficiently performing taskspecific tuning.
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