BA Allg. Sprachwissenschaft: Modul "Language and Cognition"
MA Allg. Sprachwissenschaft: Module "Language Processing", "Research Trends 1", "Research Trends 2"
BA Computerlinguistik / Computational Linguistics: Module des Wahlpflichtbereichs ASW
MA Computerlinguistik / Computational Linguistics: Module des Ergänzungsbereichs

This seminar takes a broad developmental approach to understanding the nature of human communication, examining research question in topics such as human cognitive development, neural development, language learning, language evolution, animal communication, communication theory, and social development. It also aims to develop and reinforce participants’ skills in relation to critically engaging with the research literature, and preparing and giving formal academic presentations.


For assessment purposes, students will be required to prepare and make a presentation on one of the class topics, and summarize the ideas presented in a term paper. At the end of this course, participants will have a broader understanding of linguistic and communicative development, as well as a better understanding of how to read the research literature, and how to make academic presentations.

Data structures and algorithms are core topics in linguistic programming. Data structures are used to store and retrieve data and algorithms are the recipes used to process data. This course emphasizes the understanding and Java implementation of basic data structures such as linked lists and trees, and the algorithms used to store and retrieve the information stored in them. We will see how these data structures are used in natural language processing programs.

This seminar takes an in depth look at recent approaches to characterizing human communication in terms of the discriminative properties of human learning. Whereas traditionally, linguists have considered meaning in compositional terms, discriminative linguistics treats communication as a process in which signals serve to reduce semantic uncertainty. The seminar will consider in depth what this means, relating the approach to human learning processes, as well as to Shannon’s Theory of Information, in which communication is also treated as a deductive process aimed at uncertainty reduction. As well as considering the theory and background of discriminative linguistics, the course will look a the application of discriminative models across a range of topics including language learning, morphology, speech, reading and the way that discriminative models can be used to shed light on lexical distributions.

For assessment purposes, students are required to write an extended term paper on one of the topics discussed in the course. At the end of this course, participants will have an understanding of current literature on discriminative linguistics.

The word frequency effect is one of the hallmark effects in experimental linguistics. Common words are processed faster than rare words. Recently, a number of studies has documented frequency effects of multi-word sequences as well. In this course, we will read and discuss the findings of these studies as well as the implications for our understanding of language processing. We will also work on a data set that was collected from a psycholinguistic experiment and look into the frequency effects in this data set. 

Annotated corpus resources are the primary way in which linguistic insight still feeds current computational linguistic research and applications. This seminar will provide an overview of the creation and use of linguistically annotated corpora in theoretical and computational linguistics. It will start with basic (but surprisingly non-trivial and consequential) questions such as how to tokenize or sentence segment a corpus as well as conceptual considerations relevant to the creation of annotation schemes, and will then explore different types of corpora and different types of annotations (morphological, constituency, dependency, semantic and formal pragmatic), both covering commonly used standard resources (such as the Penn Treebank) as well as linguistic corpus resources for languages other than English.

BA Allg. Sprachwissenschaft: Modul "Language and Cognition"
MA Allg. Sprachwissenschaft: Module "Language Processing", "Research Trends 1", "Research Trends 2"
BA Computerlinguistik / Computational Linguistics: Module des Wahlpflichbereichs ASW
MA Computerlinguistik / Computational Linguistics: Module des Ergänzungsbereichs

Mathematical methods are essential for understanding and working in theoretical and computational linguistics. This course introduces the key concepts from the areas of set theory, algebra and logic, which belong to the basic repertoire of linguistic methods. The main goal of the course is to provide the students with sufficient competence in basic notations, terminology and concepts of discrete mathematics for their studies in theoretical and computational linguistics. Familiarity with concepts such as sets, functions and propositions, and the ability to work with simple proof techniques are a crucial prerequisite for subsequent courses.

Students should acquire sufficient competence in basic notations, terminology and concepts of mathematics for their studies in linguistics. The topics of the course comprise the most essential mathematical notions needed in general linguistics, computational linguistics, document processing and information management. Familiarity with concepts such as sets, functions and propositions, and the ability to work with simple proof techniques will be expected in subsequent courses. The main purpose of the course is to equip the participants with the most basic mathematical tools which they will need in their linguistics courses.


  • BA Allg. Sprachwissenschaft: Modul Methods II
  • BA Computerlinguistik / Computational Linguistics: Modul Methods II

This course deals with basic concepts of morphology. Starting of with an overview of morphological typology and distinguishing morphology from other linguistic processes this course (mainly) focusses on an analysis of inflection in German, such that morphological features are correctly predicted for a feature based minimalistic syntactic analysis. This analysis includes basic concepts, such as right-hand-head rule, underspecification and feature-blocking.

In this course, we dig into the philosophy of science and principles of general design and take a look at how they apply to research in linguistics and how we think about language. We will inspect some relevant issues problem-solving humans have been running into over the last couple of millennia. Then we will use these to analyze consequences of methodology and reasoning on language research results in particular and the evolution of knowledge in general.

For class credit, you will be required to read one paper per week, ask questions in the Moodle-Forum or in class and run simple computational simulations of learning in R or Python to exemplify the problems and benefits of different approaches to problem-solving. Additionally, you can prepare a 20-minute presentation on one of the class topics or implement, visualize and write a documentation for one of the class-assignments during the semester or write a 5-page essay at the end of the semester.

This course may be fun to anyone interested in thinking and wondering and computational modeling. No prerequisites are required.

This is an introductory course to the programming language Python. In the course, we will teach the basic concepts of Python, involving elementary concepts of imperative, object-oriented programming languages. The course is aimed exclusively at BA students of General Linguistics, but is also open for students of adjacent subjects without any prior programming experience.

Given that natural languages cannot be characterized by simply listing all possible sentences and their meaning, a range of grammar formalisms have been developed to characterize form and meaning in a general and compact way. The approaches differ in terms of their focus, empirical coverage, formal foundations, expressive power, conceptualization of generalizations, and the processing regimes that have been developed for those formalisms. After a general overview of the empirical domain of syntax and the formal grammar types in the Chomsky Hierarchy, we will discuss plain context-free grammars as a baseline on which we will introduce and compare several current grammar formalisms. The plan is to include a discussion of Head-Driven Phrase Structure Grammar (HPSG), Tree Adjoining Grammars (TAG), Lexical Functional Grammar (LFG), and Combinatoric Categorial Grammars (CCG).
The focus will be on obtaining a sound working knowledge of how different formalisms capture some of the fundamental phenomena of natural language syntax.

Sentence comprehension is a classic field of research within psycholinguistics. It is concerned with the study of the cognitive processes underlying our ability to hear or read sentences. The focus is on developing theories and models about how syntactic interpretation works in realtime language processing. Research during more than fifty years has contributed strongly to our understanding of sentence comprehension processes. The present Pro-/Hauptseminar serves as an introduction to the field of sentence comprehension. We will start with classic theories and experiments on syntactic structure building and will proceed to up to date psycholinguistic models of sentence comprehension. We will end with a comparison between what is known about syntactic processing and the semantic interpretation of sentences.

When people are speaking, not all words are fully pronounced. Many acoustic forms are subject to reduction. The sentence "I don't know", for instance, is often reduced to "I dunno", or even "I ono". Recently, the phenomenon of acoustic reduction has enjoyed increased popularity in phonetic research in different languages. In this course, we will review this research to get an idea about the circumstances in which acoustic reduction occurs. Furthermore, you will gain hands-on experience by looking at acoustic reduction in actual speech data.

Texts in digital form are an essential preliminary for any subsequent analyses. The course offers a multi-faceted perspective how texts are represented in computers, with topics including (among other) character encodings (e.g. UTF-8), text structuring and data modeling (e.g. XML, HTML format), text licensing (e.g. creative commons licenses), text visualization (e.g. CSS), and text querying tools (e.g. XQUERY). the course combines a theoretical discussion with a practical approach as an illustration of of the concepts.