Summary of the paper
| Title | On the Annotation of TMX Translation Memories for Advanced Leveraging in Computer-aided Translation |
|---|---|
| Authors | Mikel Forcada |
| Abstract | The term advanced leveraging refers to extensions beyond the current usage of translation memory (TM) in computer-aided translation (CAT). One of these extensions is the ability to identify and use matches on the sub-segment level ― for instance, using sub-sentential elements when segments are sentences― to help the translator when a reasonable fuzzy-matched proposal is not available; some such functionalities have started to become available in commercial CAT tools. Resources such as statistical word aligners, external machine translation systems, glossaries and term bases could be used to identify and annotate segment-level translation units at the sub-segment level, but there is currently no single, agreed standard supporting the interchange of sub-segmental annotation of translation memories to create a richer translation resource. This paper discusses the capabilities and limitations of some current standards, envisages possible alternatives, and ends with a tentative proposal which slightly abuses (repurposes) the usage of existing elements in the TMX standard. |
| Topics | Corpus (Creation, Annotation, etc.), Machine Translation, SpeechToSpeech Translation |
Full paper  |
On the Annotation of TMX Translation Memories for Advanced Leveraging in Computer-aided Translation |
| Bibtex | @InProceedings{FORCADA14.373, author = {Mikel Forcada}, title = {On the Annotation of TMX Translation Memories for Advanced Leveraging in Computer-aided Translation}, booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)}, year = {2014}, month = {may}, date = {26-31}, address = {Reykjavik, Iceland}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-8-4}, language = {english} } |