Rohit Gupta, Constantin Orasan, Qun Liu, Ruslan Mitkov (2016). A Dynamic Programming Approach to Improving Translation Memory Matching and Retrieval using Paraphrases. In Proceedings of the 19th International Conference on Text, Speech and Dialogue (TSD), Brno, Czech Republic.
This evaluation metric is based on dense vector spaces and recurrent neural networks. In particular, the metric uses Tree Structured Long Short Term Memory networks (Tai et al., 2015) and Glove word vectors (Pennington et al., 2014). The training data is computed automatically from the WMT-13 (Bojar et al., 2013) human evaluation rankings. The rankings are converted into similarity scores between the reference and the translation. The metric has been tested on WMT-12 and WMT-14 test sets as well as participated in the WMT-15 metric task.
Constantin Orasan and Rohit Gupta (eds.) (2015) Proceedings of the First Workshop on Natural Language Processing for Translation Memories (NLP4TM 2015). Hissar, Bulgaria, 11 Sept
Gupta, R., Orasan, C., & van Genabith, J. (2015). Machine Translation Evaluation using Recurrent Neural Networks. In Proceedings of the Tenth Workshop on Statistical Machine Translation (pp. 380–384). Lisbon, Portugal.
Rohit Gupta, Constatin Orasan and Josef van Genabith (2015). ReVal: A Simple and Effective Machine Translation Evaluation Metric Based on Recurrent Neural Networks. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP-2015), Lisbon, Pourtgal,
Liling Tan, Rohit Gupta, Josef van Genabith (2015). USAAR-WLV: Hypernym Generation with Deep Neural Nets. In Proceedings of the International Workshop on Semantic Evaluation (SemEval-2015), Denver, Colorado, USA.
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.
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
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). Dubrovnik, Croatia
Hanna Bechara, Hernani Costa, Shiva Taslimipoor, Rohit Gupta, Constantin Orasan, Gloria Corpas Pastor and Ruslan Mitkov. (2015). MiniExperts: A SVM approach for Measuring Semantic Textual Similarity. In Proceedings of the 2015 Conference of the North American Chapter of the 34 Association for Computational Linguistics: Human Language Technologies, Denver, Colorado
