Automatic detection of translation errors represents one of the more promising applications of NLP techniques to this domain. This paper concentrates on one class of error, the inadvertent omission. To a greater extent than `false friends', terminological inconsistency, etc., the detection of omissions raises problems both theoretical and practical in nature. These problems are discussed, and a technique is presented for identifying possible omissions in a completed translation by employing a model of translational equivalence between words. Examples are taken from a varied corpus of French-English bitext, and illustrate how different settings of the parameters of the system affect its performance. The approach is implemented as part of a translation-checking program. 1 Introduction It has long been recognized that the provision of aids for translators is a promising area for the application of NLP techniques in the domain of translation. A recurring theme (Bashkansky et al....