Communication via language and other modalities is a fundamental component of human activity. It is therefore not at all surprising that the technologies originated from the scientific study of these activities are having a major impact on modern society. It is sufficient to think about the role played by Google in everyday life, or the crucial importance of interface design in the success of technologies such as the iPhone.
The Language and Multimodal Interaction track provides students with the interdisciplinary training necessary to operate in this area, whether in an academic environment or in an industrial setting.
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, and in interface design. Theoretical knowledge will be supplemented by the experience acquired in substantial practical projects carried out in research and industry labs. For the second year an extensive internship and a research project leading to the Master's dissertation are scheduled.
The following courses are for the a.y. 2017-2018.
This course will cover some fundamentals of algebra, probability theory, and statistics. Furthermore, the course will cover all aspects of a research project, such as sample sizes, measures, and type of experimental designs. Students will present and comment on their own research projects in progress. At the end of the course, the students should be able to design an experiment.
This module is an introduction to language science (linguistics) covering phonetics and phonology, morphology and lexical knowledge, syntax, phrase semantics, discourse, and anaphora. No previous knowledge of linguistics is required.
The course is the study of the mental processes underlying our ability to perceive, pay attention, think, categorize, use language and remember. Historically, cognitive psychology began with the information processing approach but we will also explore recent research on topics such as emotions and numerical cognition, and will include insights from neuropsychology, neuroimaging and lifespan development. The teaching methods will include demonstrations, class discussion and lectures and will emphasize the critical link between theory and experimentation. At the end of the course, students should be able to analyse critically the scientific literature on cognitive psychology topics and summarize content of a scientific article with a proper lexicon.
The course introduces the basics of computational linguistics by giving an overview of the field. It then focuses on the syntax and semantics of natural language familiarizing students with lexicalized formal grammars and computational semantics models. The second part of the course introduces students to multimodal models by considering in particular language and vision modalities. Students will hence gain a good overview of the field, its methods and main long-term goals.
This class presents a survey of methods from the fields of statistics and machine learning aimed at extracting generalizations from example data, and use them to automatically analyze new data. The class focuses on case studies in the analysis of different components of natural language.
This course provides information about the organization of the brain and its networks, focusing on the neural correlates of language and how, during the years, this knowledge has evolved. It provides also some basic information on the effects of brain lesions.
In the first part of the course, we will address how different data sources have been used in the past to draw inferences on the relationships between language and the brain, and if/how the same sources can be used to complement current neuroimaging techniques. In the second part of the course, we will focus on three topics: the functional neuroanatomy of reading/writing, and how the brain adapted to the development of written language; the neural underpinnings of (morpho) syntactic skills; the neural correlates of phonological working memory.
A general introduction to the study of meaning in natural language using the tools of formal semantics. Topics include the relation of predicate logic with natural language operators; lexical semantics, compositional semantics, nominal and verbal quantifications; modification; event semantics; genericity, and the semantics of grammatical features.
This course will examine the neural basis of higher mental functions, including brain systems supporting perception, object recognition, attention, memory, spatial functions, language, and decision-making. We will explore the neuroanatomical and neurophysiological basis of cognitive functions, considering evidence form functional neuroimaging and clinical studies. Cognitive neuroscience approaches to disorders such as autism, schizophrenia, and Alzheimer’s disease will also be explored. The teaching methods will include lectures, demonstrations, patient videos, class discussion and practical sessions in different neuroimaging labs. This first part of the course will concentrate on language, memory, perception and attentional mechanisms. At the end of the course, the students should be able to know basic topics in cognitive neuroscience and describe appropriate cognitive neuroscience methods
The course introduces how to computationally approach and manage human language technologies. The topics covered are creation of annotated corpora, syntax (e.g. parsing), semantics (e.g. similarity, word sense disambiguation), until more advanced issues of pragmatics such as affective and emotion recognition, computational treatment of persuasive and creative language. Particular attention will be given to the use of out-of-the-shelf NLP tools, so that the students can gain hands on experience.
The course introduces computer programming, focusing on those aspects that are most relevant for natural language processing. At the end of the course, the students should be able to master the computer language proposed.
Free choice courses
This course is designed for students who already have a background in the study of perception and attention. This advanced course provides an opportunity for an in-depth study of current work in perception and attention, through seminars, readings and discussions. At the end of the course the student will be able to: understand the main notions and the key problems related to the specific topic addressed in the module and to read new literature independently.
This advanced course provides an opportunity for an in-depth study of a current issues and debates in the area of cognitive neuroscience.
This course is designed for students who already have a strong background in the study of language. This advanced course provides an opportunity for an in-depth study of a particular area of language science.
The course will introduce students to neurolinguistics, and address the question of what can we learn from non invasive neurocognitive experiments about language processing in the brain. Most of the data discussed come from electropshiological and neuromiagins studies on healthy adults but theories and models will be discussed also in reference to data that comes from studies on language acquisition and loss.