29853 - Computational Linguistics (LM)

Course contents

Introduction

• Natural Language Processing - Problems and perspectives
• Basic corpus linguistics
• Fundamentals of probability calculus
• N-grams and language models

Natural Language Processing

• Machine learning techniques.
• Methods for evaluating application performances in Computational Linguistics.
• Tokenisation and sentence splitting
  
• Linguistics from a computational point of view.
  • COMPUTATIONAL PHONETICS
    
    • Audio sample properties - phones and formants
      Frequency Analysis - Spectrograms - Soprasegmental phenomena.
    • Applications for speech processing.
  • COMPUTATIONAL MORPHOLOGY
    
    • Generation and morphological analysis. Tabular lexica.
    • Techniques based on Finite State Automata.
  • COMPUTATIONAL SYNTAX
    
    • Part-of-speech tagging
    • Grammars for natural language
    • Parsing natural languages
      
    Formal grammars for language analysis
    
    • Formal languages and natural language
    • Context-free grammars
    • Dependency grammars
    • Treebanks
  • COMPUTATIONAL SEMANTICS
    
    • Lexical semantics: WordNet, FrameNet...
    • Word Sense Disambiguation
    • Distributional Semantic Models
    • Sentence semantincs and meaning representation
      
      

Readings/Bibliography

Some chapters extracted from:
- Tamburini F. (2022). Neural Models for the Automatic Processing of Italian, Bologna: Pàtron.
- Lenci, A., Montemagni, S. and Pirrelli, V. (2016). Testo e computer. Carocci.
- D. Jurafsky and J.H. Martin (2008). Speech and Language Processing, 2nd ed., Prentice Hall.
- A. Clark, C. Fox, S. Lappin (2010). The Handbook of Computational Linguistics and Natural Language Processing, Blackwell Handbooks in Linguistics.
Slides, handouts and papers downloadable from the course web site https://corpora.ficlit.unibo.it/TAL/ .

The course contents for students not attending the lessons are the same. However, students not able to attend the lessons are strongly invited to contact the teacher to get some explanations and avoid any misunderstanding about the course contents and reading materials.

Teaching methods

Face-to-face classes and laboratory sessions for 30 hours.

Assessment methods

The exam consists of an oral colloquium on the course contents designed to evaluate the critical skills and methodological knowledge gained by the student.

Reaching a clear view of all the course topics as well as using a correct language terminology will be valued with maximum rankings.
Mnemonic knowledge of the course topics or not completely appropriate terminology will be valued with intermediate rankings.
Unknown topics or inappropriate terminology use will be valued, depending on the seriousness of the omissions, with minimal or insufficient rankings.

It is compulsory to register for the exam using the online [https://almaesami.unibo.it/almaesami/welcome.htm] procedure.

Students with disabilities and Specific Learning Disorders (SLD)

Students with disabilities or Specific Learning Disorders have the right to special accommodations according to their condition, following an assessment by the Service for Students with Disabilities and SLD. Please do not contact the teacher but get in touch with the Service directly to schedule an appointment. It will be the responsibility of the Service to determine the appropriate adaptations. For more information, visit the page:
https://site.unibo.it/studenti-con-disabilita-e-dsa/en/for-students

Teaching tools

The course web site is the central point for any kind of information about the course. It contains the handouts and the readings discussed during the lessons as well as a rich software repository useful for laboratory practice.

Links to further information

https://corpora.ficlit.unibo.it/TAL/

Office hours

See the website of Fabio Tamburini