elp.moodle

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.

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. 

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.

Verwendung:

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

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.

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.