INVITED TALK: Qualitative and Quantitative Designs for Speech Translation

Qualitative and Quantitative Models of Speech Translation Hiyan Alshawi AT,~T Bell Laboratories 600 Mountain Avenue Murray Hill, NJ 07974, USA hiyan@research, at t.com Abstract This paper compares a qualitative reasoning model of translation with a quantitative statistical model. We consider these models within the context of two hy- pothetical speech translation systems, starting with a logic-based design and pointing out which of its char- acteristics are best preserved or eliminated in moving to the second, quantitative design. The quantitative language and translation models are based on relations between lexical heads of phrases. Statistical parame- ters for structural dependency, lexical transfer, and lin- ear order are used to select a set of implicit relations between words in a source utterance, a corresponding set of relations between target language words, and the most likely translation of the original utterance. 1. Introduction In recent years there has been a resurgence of interest in statistical approaches to natural language processing. Such approaches are not new, witness the statistical approach to machine translation suggested by Weaver (1955), but the current level of interest is largely due to the success of applying hidden Markov models and N-gram language models in speech recognition. This success was directly measurable in terms of word recog- nition error rates, prompting language processing re- searchers to seek corresponding improvements in per- formance and robustness. A speech translation system, which by necessity combines speech and language tech- nology, is a natural place to consider combining the sta- tistical and conventional approaches and much of this paper describes probabilistic models of structural lan- guage analysis and translation. Our aim will be to pro- vide an overall model for translation with the best of both worlds. Various factors will lead us to conclude that a lexicalist statistical model with dependency re- lations is well suited to this goal. As well as this quantitative approach, we will consider a constraint/logic based approach and try to distinguish characteristics that we wish to preserve from those that are best replaced by statistical models. Although per- haps implicit in many conventional approaches to trans- lation, a characterization in logical terms of what is be- ing done is rarely given, so we will attempt to make that explicit here, more or less from first principh's. Before proceeding, I will first examine some fashiou- able distinctions in section 2 in order to clarify the is- sues involved in comparing these approaches. I will attempt to argue that the important distinction is not so much a rational-empirical or symbolic-statistical dis- tinction but rather a qualitative-quantitative one. This is followed by discussion of the logic-based model in section 3, the overall quantitative model in section 4, monolingual models in section 5, translation models in section 6, and some conclusions in section 7. We concentrate throughout on what information about lan- guage and translation is coded and how it is express('d as logical constraints or statistical parameters. Al- though important, we will say little about search al- gorithms, rule acquisition, or parameter estimation. …

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