Automatic acquisition of salient grammar fragments for call-type classification

We present an algorithm for the automatic acquisition of salient grammar fragments in the form of finite state machines (FSMs). Salient phrase fragments are selected using a significance test, then clustered using a combination of string and semantic distortion measures. Each cluster is then compactly represented as an FSM. Flexibility is enhanced by permitting approximate matches to paths through each FSM. Multiple fragment detections are exploited by means of a neural network. The methodology is applied to the “How may I help you?” (HMIHY) call-type classification task.

[1]  Allen L. Gorin,et al.  Generating semantically consistent inputs to a dialog manager , 1997, EUROSPEECH.

[2]  Giuseppe Riccardi,et al.  How may I help you? , 1997, Speech Commun..

[3]  Andrej Ljolje,et al.  A spoken language system for automated call routing , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[4]  Enrique Vidal,et al.  Modelling (sub)string-length based constraints through a grammatical inference method , 1987 .

[5]  Allen L. Gorin,et al.  Processing of semantic information in fluently spoken language , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.