Competencies and objectives
- Course context for academic year 2017-18
- Course content (verified by ANECA in official undergraduate and Master’s degrees)
- Learning outcomes (Training objectives)
- Specific objectives stated by the academic staff for academic year 2017-18
Course context for academic year 2017-18
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). Finally, practical applications will be explained. In particular, machine translation, which has a great relevance in the current society, since we have to deal with vast amounts of information in a great number of languages.
Demand for Computational Linguistics has risen in recent years. 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.
Course content (verified by ANECA in official undergraduate and Master’s degrees)
Specific Competences (CE)
- CE1 : Understand computer terminology for specific applications and contexts applied to the languages of the speciality.
- 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.
- CE14 : Be able to decipher the main problems of linguistic processing: ambiguity, the linguistic divergences between languages, the generation of natural or genuine texts, and 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 and the main methods applied for IFE and EFE.
- CE18 : Be able to control the idiosyncratic subtleties and cultural/social differences that are essential for interpersonal relationships in academic and professional contexts (cultural values, norms 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 (argument techniques, presentation description, narrative, explanation, etc.).
- CE2 : Apply the theories, models and linguistic tools that are relevant for study and research of the IFE.
- 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 : Ability to use existing resources to obtain, handle, interpret, manage and transmit information: databases, written and oral corpora, Internet and the ICTs.
- CE26 : Ability to prepare, manage and control the quality of the applications.
- CE27 : Be able to use conventional workstations and the most generally-used applications with ease.
- CE28 : Ability to process large amounts of text using the shell and simple programming languages (awk).
- CE29 : Ability to use advanced language processing tools: morphological-syntactic analysers (part-of-speech taggers) and syntactic analysers (parsers), as well as the main lexicosemantic resources available (e.g. WordNet).
- CE3 : Apply the theories, models and linguistic tools that are relevant for study and research of the EFE.
- CE30 : Ability to process parallel and comparable multilingual corpora.
- CE31 : Ability to use automatic translators and computer-assisted translation tools intelligently and know how to assess their usefulness in academic and research contents.
- 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).
General Competences of the Degree Course:>>Instrumental: Conceptual or Cognitive
- CG1 : 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.
- CG2 : 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.
General Competences of the Degree Course:>>Instrumental: Procedural or Methodological
- CG3 : Ability to apply the knowledge acquired and solve problems in new or little-known settings within broader (or multidisciplinary) contexts related to the languages of one's speciality.
- CG4 : 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 one's knowledge and opinions in academic and research contexts.
- CG5 : Possess the ability for self-learning in the academic and research contexts associated with the languages of one's speciality.
- CG6 : Capacity to choose or design the right method of work to achieve the goals proposed in the academic and research contexts of the languages of one's speciality.
- CG7 : Capacity to communicate one's conclusions and the knowledge and reasons that support them to specialist and non-specialist audiences clearly and unambiguously in the academic and research contexts of the languages of one's speciality.
General Competences of the Degree Course:>>Instrumental: Technological
- CG8 : Use technological resources to acquire, handle, analyse, interpret and transmit information: databases, translators, spell-checkers, tools, word processors, multimedia presentations, etc.
General Competences of the Degree Course:>>Attitude: Individual
- CG10 : Capacity to work in interdisciplinary groups in international academic contexts.
- CG11 : Capacity 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 2017-18
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 such as machine translation, all of them with special emphasis on English and Spanish languages.