A Formal Basis For Spoken Language Translation By Analogy

Since spoken language is characterized by a number of properties that defy interpretation and translation by purely grammar-based techniques, recent interest has turned to analogical (also known as case-based or example-based) approaches. In this framework, the most important step consists of robustly matching the recognized input expression with the stored examples. This paper presents a probabilistic formalization of analogical matching, and describes how this model is applied to speech translation in the framework of translation by analogy. 1 I n t r o d u c t i o n The la.,~t decade has seen growing interest in the example-based framework for translation of written and spoken language (Nagao, 1984),(Jones, 1996). This approach, sometimes called analogical, casebased, or memory-based, originated with the following insight. In the course of translating an expression, a skilled human translator often recalls a similar translation that she has performed or studied before, and then carries out the new translation by analogy to the previous case, instead of applying a large number of lexical and grammatical rules in her head. In an example-based translation architecture, pairs of bilingual expressions are stored in the example database. The source language input expression is matched against the source language portion of each example pair, and the best matching example is selected. The system then returns the target language portion of the best example ms output. This is illustrated in Figure 1. BHiagusl Example Database Figure 1: Example-based Translation Architecture