TMAdvanced: A tool to retrive semantically similar matches from a Translation Memory using paraphrases
Current Translation Memory (TM) systems work at the surface level and lack semantic knowledge while matching. This tool implements an approach to incorporating semantic knowledge in the form of paraphrasing in matching and retrieval. Most of the TMs use Levenshtein edit- distance or some variation of it. This tool implements an efficient approach to incorporating paraphrasing with edit-distance. The approach is based on greedy approximation and dynamic programming. We have obtained significant improvement in both retrieval and translation of retrieved segments. More details about the approach and evaluations given in the following publications:
- Approach: Rohit Gupta and Constantin Orasan. 2014. Incorporating Paraphrasing in Translation Memory Matching and Retrieval. In Proceedings of the European Association of Machine Translation (EAMT-2014).
- Human Evaluations: Rohit Gupta, Constantin Orasan, Marcos Zampieri, Mihaela Vela and Josef van Genabith. 2015. Can Transfer Memories afford not to use paraphrasing? In Proceeding of EAMT-2015, Antalya Turkey.