CODE 55966 ACADEMIC YEAR 2026/2027 CREDITS 6 cfu anno 2 LINGUE E LETTERATURE MODERNE PER L'INSEGNAMENTO, L'EDITORIA E I MEDIA DIGITALI 11953 (LM-37 R) - GENOVA SCIENTIFIC DISCIPLINARY SECTOR INF/01 LANGUAGE Italian TEACHING LOCATION GENOVA SEMESTER 1° Semester TEACHING MATERIALS AULAWEB OVERVIEW Computational Linguistics aims at developing models and tools for natural language processing. since it combines methods and techniques from both linguistics, computer science, artificial intelligence and statistics, Computational Linguistics is interdisciplinary in nature. The scope of the discipline is therefore quite broad, and the course focuses on some of its many issues: corpus linguistics, information management, text annotation, automated and assisted translation. AIMS AND CONTENT LEARNING OUTCOMES The course aims at providing learners with the basic notions of automatic text processing, knowledge of the mechanisms behind automated translation and quantitative corpus analysis and the skills necessary to work with computer assisted translation. AIMS AND LEARNING OUTCOMES By the end of the course, students will: * have acquired foundational knowledge of computational linguistics; * be able to use computer-assisted translation (CAT) and terminology management tools; * be able to use machine translation critically and integrate it into computer-assisted translation workflows; * be able to apply post-editing and prompt-engineering techniques to translation tasks; * have acquired knowledge of the principles and techniques of information management; * have acquired knowledge of the principles and techniques of XML-based text annotation; * have developed practical skills in the use of computer-assisted translation software. PREREQUISITES none TEACHING METHODS Frontal lectures and practice SYLLABUS/CONTENT 1. Computational Linguistics and tools for linguistic analysis Introduction to Computational Linguistics Levels of analysis and linguistic annotation Tools for linguistic analysis: corpora, glossaries and concordance 2. Methods and tools for linguistic analysis and translation Text encoding Text annotation methods linguistic annotation exercises 3. Automated and Computer-assisted translation Approaches in Computer-assisted translation Post-editing Tools for Computer-assisted translation Prompt engineering and translation RECOMMENDED READING/BIBLIOGRAPHY - Alessandro Lenci, Simonetta Montemagni, Vito Pirrelli. Testo e computer - Elementi di linguistica computazionale, Carrocci, 2016. Information will be provided on AulaWeb regarding the specific chapters for the exam. - Additional materials (slides, papers, practices and tools) will be delivered through the AulaWeb portal. Further reading: - Malvina Nissim e Ludovica Pannitto, Che cos'è la linguistica computazionale, Carrocci, 2022. Textbook and readings are the same for both attending and non-attending students. TEACHERS AND EXAM BOARD SIMONE TORSANI Ricevimento: Tuesday 10-12 or by appointment ILARIA TORRE Ricevimento: By appointment Exam Board SIMONE TORSANI (President) GIANNA REGGIO ILARIA TORRE (President Substitute) LESSONS LESSONS START Monday, 5 October 2026 Time: 4:00–7:00 p.m. Room L, Polo Didattico Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION The exam consists of: written test on the course topics computer-based practical test with the final output to be uploaded for evaluation During the lecture period, exercises will be carried out that may provide additional points to the written test result. ASSESSMENT METHODS The assessment is aimed to evaluate the knowledge acquired and abilities concerning the automatic processing of texts and the management of computer-supported translation projects. Details will be provided on the course webpage of the AulaWeb platform. FURTHER INFORMATION Further details on the programme and the final exam will be published on the course Aulaweb page. Students who have officially submitted certification of a disability, specific learning disorder, or other special educational needs are advised to contact both the course disability officer, Professor Sara Dickinson (sara.dickinson@unige.it), and the course instructor at the beginning of the course, in order to agree on teaching and examination arrangements which, while respecting the learning objectives of the course, take individual learning needs into account and provide appropriate compensatory tools.
