Machine Translation of Film Subtitles from English to Spanish Combining a Statistical System with Rule - based Grammar

In this project we combined a statistical machine translation system for the translation of film subtitles from English to Spanish with rule-based grammar checking. At first we trained the best possible statistical machine translation system with the available training data. The largest part of the training corpus consists of freely available amateur subtitles. A smaller part are professionally translated subtitles provided by subtitling companies. In the next step we developed, applied and evaluated the grammar checker. We investigated if the combination of a statistical system with a rule-based grammar checker is reasonable and how we can improve the results. With the trained statistical machine translation system an application of the grammar checker would be recommendable, especially in order to correct disagreements between nouns, articles and adjectives. The precision of the grammar checker is very satisfying. With additional linguistic information, for example, syntactical information, we would probably be able to improve the grammar checker and include the correction of other kinds of errors. In addition, the evaluation showed that the improvement of the statistical machine translation system causes a significant decrease of the number of the considered errors. Furthermore, we elaborated various possibilities as to how the statistical machine translation system can be improved. Thus, one might examine, if the improvement of the system yields a significant decrease of the number of the errors. If this should be the case we have to question if the additional use of a grammar checker is still reasonable or if the number of the considered grammatical errors is too low. Additionally, we compare the performance of the trained machine translation system with the state of the art performance in the SUMAT project for the automatic translation of film subtitles from English to Spanish. According to automatic evaluation scores, the system we trained in our project was slightly better than the system of the SUMAT project. This result shows that the use of freely available amateur subtitles for the training of a statistical machine translation system for the translation of professional subtitles is recommendable, even though their quality is not optimal.