Competencies and objectives

 

Course context for academic year 2025-26

Computational linguistics is a research area within Artificial Intelligence whose objective is to automatically model humans' linguistic communication ability, that is, the language through which we communicate with each other. It is therefore an interdisciplinary field, in which linguists, computer scientists, and mathematicians, but also experts in a particular domain, such as doctors, psychologists, lawyers, etc. are needed to accurately model the specific characteristics of a specialized context.

This subject is presented as a general introduction to the basic aspects of Computational Linguistics. Its fundamentals, as well as concepts related to corpus linguistics will be studied. Also, resources and tools for computational language modeling to automatically perform different types of linguistic analysis on a text (lexical, syntactic and semantic). In addition, practical applications will be explained, which are highly relevant and useful in today's society.

Demand for Computational Linguistics has risen in recent years (https://www.expansion.com/expansion-empleo/2020/03/13/5e623166468aeb523c8b4603.html). With the increasing availability of unstructured data, companies are searching for ways to better process and understand this information. Prestigious international companies such as Facebook, Yahoo, Google, Microsoft or IBM, to name just a few, have specialised departments in Computational Linguistics, where experts in this field with different profiles create and develop new resources with the objective of improving the capacity of language understanding and generation in an automatic manner.

 

 

Learning outcomes / Course competencies (verified by ANECA in official undergraduate and Master’s degrees) for academic year 2025-26

Skills/Skills

  • CE02 : Apply the theories, models and linguistic tools that are relevant for study and research of the IFE.
  • CE03 : Apply the theories, models and linguistic tools that are relevant for study and research of the EFE.
  • CE10 : Use the perspectives, models and analysis techniques that are essential to construct the theoretical framework of Computational Linguistics.
  • CE11 : Use the perspectives, theories and analysis techniques that are essential for constructing the theoretical framework of Forensic Linguistics.
  • CE12 : Use specific computer programs and tools for analysing texts and researching into Computational Linguistics.
  • CE13 : Use specific computer programs and tools for analysing texts and researching into Forensic Linguistics.
  • CE28 : Ability to process large text collections using the command interpreter (shell) and simple programming languages (awk).
  • CE29 : Ability to use advanced language processing tools: morphological-lexical analysers (part-of-speech taggers) and syntactic analysers (parsers), as well as the main lexical-semantic resources available (e.g. Word Net).
  • CE31 : Ability to use machine translators and computer-assisted translation systems intelligently, and know how to evaluate their usefulness in academic and research contexts.
  • CG03 : Ability to apply acquired knowledge and solve problems in new or unfamiliar environments within broader or multidisciplinary contexts related to specialised languages.
  • CG08 : Use technological resources to obtain, manage, analyse, interpret and transmit information: databases, translators, proofreaders, tools, word processors, multimedia presentations, etc.

 

Conocimientos/Contenidos

  • CE01 : Knowledge of computer terminology in specific applications and environments applied to specialised languages.
  • CG01 : Know how to apply the main perspectives, theories, techniques and analysis models in the field of interdisciplinary research of linguistics applied to the study of the IFE.
  • CG02 : Know how to apply the main perspectives, theories, techniques and analysis models in the field of interdisciplinary research of linguistics applied to the study of the EFE.
  • CG04 : Know how to integrate knowledge and deal with the complexity of giving opinions on the basis of information that may be incomplete or limited and includes reflections on the social and ethical responsibilities associated with applying their knowledge and judgements in academic and research contexts.
  • CT2 : Achieve a critical understanding of the complexity of socio-environmental challenges and problems, including the roots of gender inequalities, situations of discrimination and social exclusion, threats to peace and the achievement of human rights, as well as environmental challenges.

 

Skills/Competences

  • CE14 : Be able to decipher the main problems of linguistic processing: ambiguity, the linguistic divergences between languages, the generation of natural or genuine texts, or the need to encode and manage large amounts of information to construct the processors.
  • CE15 : Be able to synthesise the stages of analysis of a human language processing system (morpholexical, syntactic-semantic and pragmatic), the main problems, as well as the main methods applied and the tools developed for the IFE and the EFE.
  • CE18 : Be able to control the idiosyncratic subtleties and cultural and social differences that are essential for interpersonal communication in academic and professional settings (cultural values, rules of courtesy, non-verbal communication, etc.).
  • CE19 : Be able to use the communicative and discursive techniques common to most of the discourses of the speciality, which serve to achieve different communicative purposes (techniques of argumentation, exposition, description, narration, explanation, etc.).
  • CE21 : Be able to analyse the discourses constructed using the languages of the speciality, in English and Spanish, and establish their qualities and deficiencies according to the parameters studied from different linguistic perspectives.
  • CE23 : Be able to identify the determining features of the voice in oral texts in English and Spanish.
  • CE24 : Be able to write reports and expert linguistic findings.
  • CE25 : Be able to use existing resources to obtain, handle, interpret, manage and transmit information: databases, written and oral corpora, Internet and ICTs.
  • CE26 : Ability to prepare, manage and control the quality of the applications.
  • CE27 : Be able to use a conventional workstation and the most common applications with ease.
  • CE30 : Ability to handle parallel and comparable multilingual corpora.
  • CE33 : Ability to give an academic presentation orally in English and Spanish in academic and research contexts.
  • CE34 : Ability to identify linguistic or interdisciplinary research problems related to some variety of IFE.
  • CE35 : Ability to identify linguistic or interdisciplinary research problems related to some variety of EFE.
  • CE36 : Ability to apply linguistic knowledge to researching some aspect related to the languages of the speciality (English and Spanish).
  • CE37 : Ability to apply the knowledge acquired of ICTs to research into aspects related to the languages of the speciality (English and Spanish).
  • CG05 : Possess the ability to develop self-learning in academic and research environments in specialised languages.
  • CG06 : Ability to choose or design the appropriate working method to achieve the proposed objectives in academic and research environments in specialised languages.
  • CG07 : Ability to communicate their conclusions and the knowledge and ultimate reasons behind them to specialist audiences in a clear and unambiguous manner in academic and research environments of specialised languages.
  • CG10 : Ability to work in interdisciplinary teams in international academic contexts.
  • CG11 : Ability to adapt to new situations.
  • CG12 : Ethical commitment.

 

 

 

Learning outcomes (Training objectives)

  • Conocimiento de los fundamentos básicos y tecnologías disponibles, que capaciten para el aprendizaje y análisis de herramientas relacionadas con la Lingüística Computacional.
  • Capacidad para analizar y valorar herramientas de Lingüística Computacional con iniciativa, toma de decisiones, autonomía y creatividad.
  • Capacidad para recopilar y analizar corpus de datos con iniciativa, toma de decisiones, autonomía y creatividad.
  • Capacidad para saber comunicar y transmitir los conocimientos, habilidades y destrezas de las tareas propias de un Lingüista Computacional.

 

 

Specific objectives stated by the academic staff for academic year 2025-26

The aim of this course is that students learn basic but sufficient knowledge about Computational Linguistics, from a strongly computational perspective focused on automatic corpus analysis, computational modeling of natural language, existing tools and current applications, all of them with special emphasis on English and Spanish languages.

 

 

General

Code: 38610
Lecturer responsible:
Lloret Pastor, Elena
Credits ECTS: 6,00
Theoretical credits: 0,00
Practical credits: 2,40
Distance-base hours: 3,60

Departments involved

  • Dept: Spanish Philology, General Linguistics and Theory of Literature
    Area: Spanish Language
    Theoretical credits: 0
    Practical credits: 1,2
  • Dept: Software and Computing Systems
    Area: Languages and Computing Systems
    Theoretical credits: 0
    Practical credits: 1,2
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.

Study programmes where this course is taught