Lexical Functional Grammar in Speech Recognition

Lexical Functional Grammar in Speech Klaus Jiirgen Engelberg Fraunhofer Institut IAO Holzgartenstr. 17 D 7000 Stuttgart West Germany Recognition Abstract ~he syntax component of the speech recognition system IKAROS t is described, clhe usefidness of a probabilistic Le~jcal Functional Grammar both for cow,straining bottom-up hypotheses and top-down predicting is showtL 1. Introduction The most important problem in all speech recognition systems is the inherent uncertainty associated with the acoustic-phonetic decoding process at the basis of such a system. One approach taken in many existing system to overcome these difficulties is to integrate higher level knowledge sources that have a certain a-priori knowledge about specific problem areas. Following this line of thought, the system architecture adopted in the IKAROS-project assumes different levels of knowledge (representations) e.g. acoustic parameters, phonemes, words, constituent structures etc. The interaction between these knowledge sources is controlled by a central blackboard control module (like in HEARSAY II). This whole system is embedded in an object- oriented environment and communication between the modules is realized by message passing. Within IKAROS particular attention is given to the problem of using the same knowledge representations both for data-driven bottom-up hypothesizing and expectation-driven top-down prediction and to the problem of providing a general framework of uncertainty management. According to this rationale, the main purpose of the syntax component is to constrain the number of word sequences to be dealt with in the recognition process and to predict or insert poorly recognized words. Grammaticaless in itself is of no importance to us. Quite to the contrary, in a real-live application a certain degree of error tolerance is a desired "effect. 1 Research in IKAROS is partially funded by the ESPRIT programme of th6 European Community under contract P954 In the syntax component of IKAROS we work within the formal framework of a probabilistic Lexical Functional Grammar. Certain modifications to the formalism as expounded in /Bresnan1982/ have been made to suit our purposes. We use as an implementation an event-driven chart-parser that is capable of all the necessary parsing strategies i.e. top-down, bottom-up and left-to-right and right- to-left parsing. 2. Probabilistic context.free Grammars 2.1. The event-driven parser The interaction between the blackboard manager and the syntax component is roughly as follows: the blackboard manager sends a message to the syntax component indicating that a particular word has been recognized (or rather "hypothesized") at a certain position in the input stream (or in charto parser terminology with starting and ending verte~ ~ number) together with a certain numerical confidence score. The syntax component accumulates information about these (in arbitrary order) incoming word hypotheses and in turn posts hypotheses about predicted and recognized words or constituents on the blackboard. The job of the syntax component now is to decide between several conflicting (or competing) constituent structures stored in the chart i.e. to choose the best grammatical structure. 2.2. The formalism We assume a probabilistic context-free grammar G=<VN, VT, R,S>: VN denotes the nonterminal vocabulary Nonterminals are denoted by A, B, C .... strings of these …

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