TT2 is an innovative tool for speeding up and facilitating the work of translators by automatically suggesting translation completions. Different versions of the system are being developed for English, French, Spanish and German by an international team of researchers from Europe and Canada. Two professional translation agencies are currently evaluating successive prototypes. 1

Although Machine Translation (MT) is a very active research field which is receiving an increasing amount of attention from the research community, the results that current MT systems are capable of producing are still quite far away from perfection. Because of this, and in order to build systems that yield correct translations, human knowledge must be integrated into the translation process, which will be carried out in our case in an Interactive-Predictive (IP) framework. In this paper, we show that considering Mouse Actions as a significant information source for the underlying system improves the productivity of the human translator involved. In addition, we also show that the initial translations that the MT system provides can be quickly improved by an expert by only performing additional Mouse Actions. In this work, we will be using word graphs as an efficient interface between a phrase-based MT system and the IP engine. 1

Compared to the telephone, email based customer care is increasingly becoming the preferred channel of communication for corporations and customers. Most email-based customer care management systems provide a method to include template texts in order to reduce the handling time for a customer’s email. The text in a template is suitably modified into a response by a customer care agent. In this paper, we present two techniques to improve the effectiveness of a template by providing tools for the template authors. First, we present a tool to track and visualize the edits made by agents to a template which serves as a vital feedback to the template authors. Second, we present a novel method that automatically extracts potential templates from responses authored by agents. These methods are investigated in the context of an email customer care analysis tool that handles over a million emails a year. 1

Abstract. We investigate novel types of assistance for human translators, based on statistical machine translation methods. We developed the computer aided tool Caitra that makes suggestions for sentence completion, shows word and phrase translation options, and allows postediting of machine translation output. We carried out a study of the translation process that involved non-professional translators that were native in either French or English and recorded their interaction with the tool. Users translated 192 sentences from French news stories into English. Most translators were faster and better when using assistance. A detailed examination of the logs also provides insight into the human translation process, such as time spent on different activities and length of pauses.