Call for papers Workshop on Data-driven MT ACL'2001 Conference Toulouse, France Invited speaker: Hermann Ney, RWTH Aachen Deadline for paper submissions: April 6, 2001 Deadline for notification of paper acceptance: April 27, 2001 Deadline for camera-ready papers: May 16, 2001 Workshop Date: July 7, 2001 Details on submissions listed below. With the increased availability of online corpora, data-driven approaches have become central to the NL community. A variety of data-driven approaches have been used to help build Machine Translation systems -- example-based, statistical MT, and other machine learning approaches - and there are all sorts of possibilities for hybrid systems. We wish to bring together proponents of as many techniques as possible to engage in a discussion of which combinations will yield maximal success in translation. We propose to center the workshop on Data Driven MT, by which we mean all approaches which develop algorithms and programs to exploit data in the development of MT, primarily the use of large bilingual corpora created by human translators, and serving as a source of training data for MT systems. We are specifically interested in papers about * statistical machine translation (modeling, training, search) * machine-learning in translation * example-based machine translation * acquisition of multilingual training data * evaluation of data driven methods (also with rule-based methods) * combination of various translation systems; integration of classical rule-based and data driven approaches * word/sentence alignment methods An especially important question that we wish to address is which techniques are best for each of the subparts of a complete MT system - e.g. learning grammars, building lexicons, parsing input data, determining transfer principles, generating target text, etc. We will strongly encourage papers on systems which show demonstrable progress over previously chosen methods, and which have been integrated in an actual end-to-end system. Test results or demos will be given strongest preference for participation. Organizers: Jessie Pinkham, Microsoft Research jessiep@microsoft.com