Use of intonational phrase boundaries to select syntactic hypotheses in a speech understanding system

Abstract

A procedure has been developed for using prosodically detected phrase boundaries to weight word and phrase hypotheses in the Bolt Beranek and Newman (BBN) SPEECHLIS speech understanding system, so that correct words and structural hypotheses will be proposed at earlier stages in parsing, and erroneous theories can be avoided. The state-transition arcs of the augmented transition network grammar were specially marked if they were expected to be immediately preceded by intonationally detected phrase boundaries. The scores on words associated with the arcs were increased if expected boundaries were detected, or decreased if expected boundaries were missing in the acoustic-prosodic darn. Fifteen BBN sentences were processed through a computer program that detected phrase boundaries at fall-rise valleys in fundamental frequency contours. Analysis of simple traces of the hypothesizing, testing, and constructing of syntactic structures by the SPEECHLIS system showed that prosodic adjustment of scores would increase the likelihood of correct words and phrases being selected before incorrect ones. These ideas are being refined and tested further, for implementation in the SPEECHLIS system.