Compared with English learners, Spanish learners have fewer resources for automatic error detection and revision and following the current integrative Computer Assisted Language Learning ( CALL ), we combined corpus-based ap proach and CALL to create the System of Error Detection and Revision Suggestion ( SEDRS ) for learning Spanish. rough corpus-based data training and related applications, this system was designed specially for learners of Spanish in Taiwan. e Corpus of Taiwanese Learners of Spanish ( CTLS ) was used as a database to facilitate the development of the system. e learners' corpus was tagged with part-of-speech ( POS ) and lemma information, and it was also anno- tated by native Spanish speakers with revisions corresponding to errors made by students in their original texts. e system can, in real time, identify tri-gram errors based on train- ing data extracted from the revised texts of the learners' corpus and provide revision sugges- tions listed according to usage frequency for users. e system was evaluated by Spanish learners and eight experienced programmers to quantify the system's practical e ectiveness. In addition, feedback from learners' was col - lected to improve the system in the future.
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