Specialization: Computacional Linguistics

Computational Linguistics addresses the study of language and the development of linguistic applications with computational means. This track offers a general introduction to the field, presenting the main theoretical and methodological approaches to Natural Language Processing, as well as an overview of several Computational Linguistic applications. It is based on a hands-on approach in which students develop basic skills for data processing and analysis, as well as the use and evaluation of computational models.

This track will allow you to:

• understand the main research issues in Natural Language Processing, including Machine Learning methods,
• acquire basic skills for approaching practical work in Natural Language Processing.

The course instructors of this track are active researchers in the field, and have extensive experience in teaching this subject to students with diverse backgrounds, including the Humanities, where the background training does not usually cover formal and quantitative methods.

Important: For some subjects of the Computational Linguistics track, programming at a basic level is required (see “Programming skills” section below).

Learning goals

Courses

In addition to the three core advanced foundational courses of the master (Syntax, Semantics and pragmatics, and Phonetics and Phonology), there are two specific specialisation courses for Computational Linguistics (taught each year):

• Natural Language Processing
• Computational Semantics

In addition, two of the methodology courses that are taught each year are highly recommended for students on the Computational Linguistics track, as they provide knowledge and skills within the relevant area of knowledge:

• Corpora and computational tools
• Experimental and observational techniques

Additionally, a Levelling course on basic programming in Python is offered to students that want to refresh their programming skills, and the course Natural Language Interaction, from the Master’s in Intelligent Interactive Systems, is also available as an elective course for the students that meet its enrollment requirements.

Completion of the M.A. requires the writing of a Master’s thesis which is worth 15 ECTS credits. The thesis is typically supervised by one or two Computational Linguistics instructors.
 

Language of instruction

The Computational Linguistics track courses are taught in English. Students must have enough language skills in English to be able to follow the lectures and participate in class. Exceptionally, written work can be submitted in other languages if permission is previously granted by the instructors.
 

Programming skills, recommendations

We will be using Python, and we expect students to acquire basic skills before the start of the first term (e.g. during the summer prior to the start of the Master’s). If you don’t already have basic skills, we recommend the free online resource Python for Everybody, lessons 1-12, including the exercises. The course requires around 2 hours per lesson. (You are of course welcome to use other learning resources with equivalent contents, such as this MIT course.) After going through these materials, you are expected to take the Levelling course mentioned above; please bear in mind that the Levelling course does not substitute the aforementioned training and that you are expected to take both.

There will be a tutoring session at the beginning of September where you can talk to your tutor about how to tailor the programming training to your needs. Note that if you have not acquired basic Python skills by the time the Master’s starts, you will not be able to follow all the courses of the specialization.

Employment and Professional Outcomes

Computational linguists are currently in high demand, in particular for the development of virtual assistants and chatbots, as they typically both have linguistic skills in more than one language and master natural language processing techniques. Employers seek professionals that can design dialog systems and build grammars and other language resources for the analysis and generation of conversations adequate for different types of customer services.

Computational linguists are also employed to assist in the development of machine learning and deep learning systems applied to natural language processing. They are expected to master the necessary methodology and tools to annotate texts with different types of linguistic and extralinguistic knowledge, as well as to be able to quantitatively and qualitatively evaluate the output of the computational systems. They are also commonly employed as Data Scientists for linguistic data, for instance in areas such as Opinion Mining (finding out what people think about given products or organizations).

The Master's Computational Linguistics track offers three specialized courses, which provide a basic introduction to the aforementioned skills and techniques. Depending on their background, the students may need to autonomously acquire further skills to be employed as a computational linguist.

The following companies have employed our alumni: Nuance Communications, Everis, Telefonica, Expert Systems, Inbenta, StratioBD, ForceManager and Amazon.