a multimodal predictive-interactive application for computer assisted transcription and translation
Traditionally, Natural Language Processing (NLP) technologies have mainly focused on full automation. However, full automation often proves unnatural in many applications, where technology is expected to assist rather than replace the human agents. In consequence, Multimodal Interactive (MI) technologies have emerged. On the one hand, the user interactively co-operates with the system to improve system accuracy. On the other hand, multimodality improves system ergonomics. In this paper, we present an application that implements such MI technologies. First, we have designed an Application Programming Interface (API), featuring a client-server framework, to deal with most common NLP MI tasks. Second, we have developed a generic client application. The resulting client-server architecture has been successfully tested with two di erent NLP problems: transcription of text images and translation of texts.
multimodality interactive framework handwritten recognition machine translation