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COMPUTATIONAL LINGUISTICS AND COMPUTER-ASSISTED TRANSLATION

CODE 55966
ACADEMIC YEAR 2022/2023
CREDITS
  • 6 cfu during the 1st year of 8743 TRADUZIONE E INTERPRETARIATO (LM-94) - GENOVA
  • SCIENTIFIC DISCIPLINARY SECTOR INF/01
    LANGUAGE Italian
    TEACHING LOCATION
  • GENOVA
  • SEMESTER 2° 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

    Students will learn:
    the fundamentals of Computational Linguistics and the principles of automated and computer-assisted translation
    the principles and techniques for information management
    the principles and techniques for text annotation through XML
    the skills necessary to work with computer-assisted transaltion and terminology management

    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

    RECOMMENDED READING/BIBLIOGRAPHY

    - Alessandro Lenci, Simonetta Montemagni, Vito Pirrelli. Testo e computer - Elementi di linguistica computazionale, Carrocci, 2016.

    - Malvina Nissim e Ludovica Pannitto, Che cos'è la linguistica computazionale, Carrocci, 2022.

    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.

    Textbook and readings are the same for both attending and non-attending students.

    TEACHERS AND EXAM BOARD

    Exam Board

    ILARIA TORRE (President)

    SIMONE TORSANI

    LESSONS

    LESSONS START

    SECOND SEMESTER

    Lessons will start the first week of the second semester, on 16th February 2023.

    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.

    Exam schedule

    Date Time Location Type Notes
    17/01/2023 11:00 GENOVA Scritto + Orale Aula G
    10/02/2023 14:00 GENOVA Scritto + Orale Aula G
    05/05/2023 11:00 GENOVA Scritto Aula L
    05/05/2023 11:00 GENOVA Orale Aula L
    16/06/2023 10:00 GENOVA Scritto + Orale Aula G
    17/07/2023 14:00 GENOVA Scritto + Orale Aula G

    FURTHER INFORMATION

    Students with disabilities or learning disorders are suggested to contact the teachers. They are allowed to use specific modalities and supports that will be determined on a case-by-case basis.