Defining constraints for multilinear speech processing

This paper presents a constraint model for the interpretation of multilinear representations of speech utterances which can provide important fine-grained information for speech recognition applications. The model uses explicit structural constraints specifying overlap and precedence relations between features in both the phonological and the phonetic domains in order to recognise well-formed syllable structures. In the phonological domain, these constraints together form a complete phonotactic description of the language, while in the phonetic domain, the constraints define the internal structure of phonologial features based on phonetic realisations. The constraints are enhanced by a constraint relaxation procedure to cater for underspecified input and allows output representations to be extrapolated based on the phonetic and phonological information contained in the constraints and the rankings which have been assigned to them. This approach thus addresses issues of robustness in speech recognition.