This paper outlines the general strategies followed in developing the CMU (Carnegie Mellon University) speech understanding system. Our system is oriented toward the extraction of information relevant to a task. It uses a flexible frame-based parser. Our system handles phenomena that are natural in spontaneous speech, for example, restarts, repeats and grammatically ill-formed utterances. It maintains a history of the key features of the dialogue. It can resolve elliptical, anaphoric and other indirect references. In this paper, we pay particular attention to how the context is modeled in our system. We will describe how the system handles corrections and queries that execeed its capabilities. We also address the issue of loose vs. tight coupling of speech recognition and natural language processing. The system has been used to model an Air Travel Information Service (ATIS) Task. In the November 92 DARPA Spoken Language Systems benchmark evalua- tion, the CMU ATIS system correctly answered 93.5% transcript inputs and 88.9% speech inputs. These were the best numbers reported for the evaluation.
Keywords: Spontaneous Speech, Flexible Parser, Dia- logue, Loose vs. Tight Coupling, Corrections
Bibliographic reference. Issar, Sunil / Ward, Wayne (1993): "CMLPs robust spoken language understanding system", In EUROSPEECH'93, 2147-2150.