Abstract
A semiautomated methodology for eliciting knowledge from an expert is described. The methodology suggests the use of a manual interview technique and the application of a machine learning program to structure the elicited information. This way the experts are free to express their knowledge in a familiar format. Automated processing helps the knowledge engineer formalize knowledge. This interaction between manual and automatic techniques is particularly useful when the expert meets with difficulties in formulating general rules and prefers, instead, to reason by cases. The application of the methodology to an image interpretation task, namely speech spectrogram reading, is described as a test case.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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