Language is widely recognized as part of what makes us human, and we instinctively know its value in communication and in the development of ideas. However, transferring those skills to computers has been anything but easy.
That is the challenge of Language and Communication Technologies, a dynamic discipline which joins Linguistics and Computer Science.
Language technologies are information technologies that are specialized for dealing with human language. Therefore these technologies are also often subsumed under the term Human Language Technology. Human language occurs in spoken and written form. Whereas speech is the oldest and most natural mode of language communication, complex information and most of human knowledge is maintained and transmitted in written texts. Speech and text technologies process or produce language in these two modes of realization. But language also has aspects that are shared between speech and text such as dictionaries, most of grammar and the meaning of sentences. Thus large parts of language technology cannot be subsumed under speech and text technologies. Among those are technologies that link language to knowledge. We do not know how language, knowledge and thought are represented in the human brain. Nevertheless, language technology had to create formal representation systems that link language to concepts and tasks in the real world. This provides the interface to the fast growing area of knowledge technologies.
In our communication we mix language with other modes of communication and other information media. We combine speech with gesture and facial expressions. Digital texts are combined with pictures and sounds. Movies may contain language and spoken and written form. Thus speech and text technologies overlap and interact with many other technologies that facilitate processing of multimodal communication and multimedia documents. In this respect, the investigation and modelling of human language is a truly interdisciplinary endeavor. That is, the methods of language technology come from several disciplines: computer science, computational and theoretical linguistics, mathematics, electrical engineering and psychology.
As such, language and communication technologies occupy a central position in research and education in Europe. They are the key enabling technologies for numerous applications related to the information society, including multilingual document production and management, intelligent web search and semantic web, voice control of electronic equipment, automated dialog, and language learning. The market is growing rapidly, although the shortage of qualified researchers and developers is slowing down the speed of innovation in Europe.
The Center for Mind/Brain Sciences (CIMeC), is offering the European Masters Program in Language and Communication Technologies (EM LCT), as part of an international joint program organized by a consortium of universities.
One of the few such programs in the world, the EM LCT was designed with input from industry professionals and researchers of cutting edge universities to give students a solid foundation in language and communication technologies so that they will be able to grow and change along with this rapidly developing and exciting discipline. Students will gain knowledge of fundamental techniques in speech and language processing and their application in domains such as semantic web, digital libraries, natural language processing (e.g. question answering, dialogue systems, machine translation) and information retrieval.
- 2 year Master's program taught in English: recognized as a program of excellence by the EU Commission (Erasmus Mundus) and running since 2006;
- LCT: an attractive and rapidly-expanding field of computational linguistics and language technologies;
- Erasmus Mundus Scholarships: available for both EU and non-EU students;
- Distributed and joint program: students spend each year in a different institution of the consortium following a joint study plan with compulsory modules and advanced modules complemented by a Project and a Master thesis, for a total of 120 ECTS credits;
- Double degree: students completing the program obtain an EM LCT diploma, plus two degrees legally recognized in each of the countries where the student has studied;
- Job opportunities: graduates of the EM LCT will bring to businesses, industry and the research world the expertise needed to improve the nexus between humans and machines.
Why study at UniTrento
The University of Trento (UniTN) is one of the most dynamic and ambitious universities in Italy. Although only 50 years old, it has established itself as a center for excellence in both research and teaching, as testified by the annual University League Tables of the "Repubblica" newspaper, according to which all UniTN Departments occupy either the first or the second position in Italy. UniTN is also extremely active in the European and international context, achieving very high levels of funding both in terms of research (it is among the top three Universities in Italy in terms of EU projects) and in terms of teaching (the University is involved in numerous European Masters and double degrees).
LCT has been a traditional area of strength in the Trento area, ever since the establishment over twenty years ago of a Natural Language Processing research group at ITC-IRST, now Fondazione Bruno Kessler (FBK) where there is now active a Research Unit on Human Language Technology (HLT). In recent years, UniTN started to invest heavily in the area of Language and Communication as well, developing both the technological and the scientific side. Two research groups have been established: the Language Speech and Interaction group (LSI) at DISI, with primary focus on technology, and the Language, Interaction and Cognition lab (CLIC) of CIMeC. Research on LCT is also carried out at DIPSCO, with a strong focus on the basic science of language and communication, and at the Laboratory for Applied Ontology of ISTC-CNR (LOA-ISTC-CNR) where attention is focused on basic and applied research on the ontological foundations of knowledge with a strong interdisciplinary approach, including language and computer sciences.
The Trento approach to LCT is characterized by a strong interdisciplinary focus, enabled by the strict collaboration with cognitive neuroscientists at CIMeC as well as close contacts with the growing Computer Vision research community. The latter supports the multimodal content analysis and the analysis of user behavior through visual cues.
UniTN is active part of the larger network of research labs focusing on Natural Language Processing and related domains in the Trento region, that is quickly becoming one of the areas with the highest concentration of researchers in NLP and related knowledge mining fields.
This activity also led to the establishment of a community of small and medium enterprises operating in the area and gathered in the Semantic Valley consortium; many of such companies operate in the LCT field, such as COGITO, CLS, OKKAM, PerVoice.
The CIMeC is located in the beautiful city of Rovereto, surrounded by the Alps and famous for its culture, the quality of life, and the range of outdoors sport and relax opportunities it offers.
Within the Master's course in Cognitive Science (Laurea Magistrale in Scienze Cognitive), UniTN offers the Language and Multimodal Interaction track (LMI). Particular strenghts of this track, that distinguish it from those offered by the other partners of the EM LCT, is the focus on Language and Vision, as well as the chance to study topics in Cognitive Neuroscience and Neuroimaging.
Students studying in Trento will have the possibility to focus on the integration of computational and cognitive models of Language and Vision, learning to evaluate them against subject behaviors and neuroscientific data in semantic tasks such as perception, categorization, classification and composition. Students will learn on the one hand to better understand the interaction between language and vision in human conceptual knowledge, and on the other to develop systems able to extract information jointly from images and text, as well as to develop resources that could be integrated in information retrieval systems searching for texts and/or images.
The track is designed to meet the demands of industry and research in a rapidly growing area. Students will learn to apply their computer science knowledge to make computers manage natural language texts and images. The two-year Master's course combines a solid foundation in scientific and cognitive methods - modules in mathematics, language science, neuroscience, and psychology, including an introduction to advanced methods such as eye tracking, EEG, and fMRI - with an extensive training in computational methods for the statistical analysis of large amounts of language and perceptual data. Theoretical knowledge will be supplemented by the experience acquired in substantial practical projects carried out in research and industry labs.
Courses and study plan
Students will have to agree on their individual study program with the LCT local coordinator professor Raffaella Bernardi; courses will be assigned on the base of the students interest and the partner university where they study.
For more information about the courses held at UniTN:
- Educational Offer, Academic Year 2018-2019;
- Academic Calendar, Academic Year 2018-2019;
- Schedule of lessons (by degree, by teacher, by course), Academic Year 2018-2019;
- Teaching activities (please select CIMeC from the drop-down menu), Academic Year 2018-2019;
- Exams calendar (by degree, by teacher, by course), Academic Year 2018-2019;
- UniTrento courses and EM LCT modules correspondence;
- Research and thesis projects;
Students will have the possibility of carrying out their research project (15 ECTS) and Master Thesis (30 ECTS) within the many research centers and medium and large companies in the Trentino Valley.
There are several dates throughout the year at which a student may choose to graduate. These dates are known as degree sessions. It is the responsability of the student to submit the necessary paperwork in order to graduate at the date they chose.
Who should apply for Trento?
Students applying for Trento should have a solid background in computer science, ideally including good programming skills, knowledge of algorithms and optimization techniques, basic math and statistics. The students should have an interest in human cognition, in particular the core human faculties to perceive the world with vision and communicate about it via natural language, and they should be curious about interdisciplinary topics at the boundary of computer and cognitive neuro-science and their applications in advanced intelligent applications.