Paper
1 January 1990 Oral task-oriented dialogue for air-traffic controller training
Abdel-Karim Matrouf, Jean-Luc Gauvain, Francoise Neel, Joseph J. Mariani
Author Affiliations +
Abstract
We present here an oral dialogue system designed for air-traffic controller training. The system has to handle the dialogue with a student air-traffic controller and communicate the student’s requests to the air-traffic simulator in the form of a sequence of instructions expressed in a formal command language. The system has been developed with two main objectives in mind: we tried to make it both user-friendly and robust. Different knowledge sources including the vocabulary, the phraseology, the task model and the history of dialogue, are evolving during the dialogue. These knowledge bases are represented in a unified form of hierarchical frames. The message analysis and interpretation consist of two phases: categorisation and instantiation. Then, a validity control process uses a set of semantico-pragmatic constraints. Correction procedures have also been developed to improve speech recognition performance. The speech recognition system which is being used is AMADEUS developed at the LIMSI. It is a DTW-based continuous speech recognizer. The representation of the language model used to limit the DTW search space is described as well as the way it is modified by the dialogue manager in order to permit or prohibit messages and improve recognition. In system evaluation, the classical DTW approach is compared to a probabilistic approach using dynamically updated transition probabilities.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Abdel-Karim Matrouf, Jean-Luc Gauvain, Francoise Neel, and Joseph J. Mariani "Oral task-oriented dialogue for air-traffic controller training", Proc. SPIE 1293, Applications of Artificial Intelligence VIII, (1 January 1990); https://doi.org/10.1117/12.21132
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CITATIONS
Cited by 2 scholarly publications and 1 patent.
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KEYWORDS
Artificial intelligence

Speech recognition

Acoustics

Device simulation

Detection and tracking algorithms

Evolutionary algorithms

Telecommunications

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