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The Air Travel Information System (ATIS) domain serves as the common evaluation task for ARPA"spoken language system developers. 1 To support this task, the Multi-Site ATIS Data COllection Working group (MADCOW) coordinates data collection activities. This paper describes recent MADCOW activities. In particular, this paper describes the migration of the(More)
The Air Travel Information System (ATIS) domain serves as the common task for DARPA spoken language system research and development. The approaches and results possible in this rapidly growing area are structured by available corpora, annotations of that data, and evaluation methods. Coordination of this crucial infrastructure is the charter of the(More)
This paper describes work in progress to develop a facility for natural language access to a variety of computer databases and database systems. This facility, called IRUS for Information Retrieval using the RUS parsing system, allows users who are unfamiliar with the technical characteristics of the underlying database system to query databases using typed(More)
Prognostication is a dangerous business. Doing it in print is even more dangerous. Unless your predictions are luckily, spectacularly right, people in the future will read your milder (but correct) predictions with a yawn and, worse, your failures with amusement. The way to protect your dignity, of course, is not to make real predictions, but merely to(More)
There has been a long-standing methodology for evaluating work in speech recognition (SR), but until recently no community-wide methodology existed for either natural language (NL) researchers or speech understanding (SU) researchers for evaluating the systems they developed. Recently considerable progress has been made by a number of groups involved in the(More)
We present results from the February '92 evaluation on the ATIS travel planning domain for HARC, the BBN spoken language system (SLS). In addition, we discuss in detail the individual perfor-2. mance of BYBLOS, the speech recognition (SPREC) component. In the official scoring, conducted by NIST, BBN's HARC system 3. produced a weighted SLS score of 43.7 on(More)
BBN's project in Knowledge Representation for Natural Language Understanding is developing techniques for computer assistance to a decision maker who is collecting information about and making choices in a complex situation. In particular, we are designing a system for natural language control of an intelligent graphics display. This system is intended for(More)