This course will introduce you to the exciting world of Large Language Models (LLMs) and their applications in linguistic research. You will start by learning the basics of LLMs, including their architecture, capabilities, and limitations.
Laboratory Phonology is the approach to studying phonology--the sound patterns in language--by using experiments. In this course, we will be particularly interested in answering questions about phonology using data from phonetics. Students will work together to conduct an original experimental study. Skills required to conduct the study will be taught and practiced during the course. The basic outline of the study will be provided, but we will develop the details during the semester. Students will develop the experiment design, conduct recordings, take measurements, analyze data, and interpret results. Students will use equipment in the new Computational Phonetics lab in order to conduct the class experiment. Students should expect to work in collaboration with classmates, and active participation in every stage of the course is required for BN credit. Participation in class activities is expected and required.
Language and Health is a seminar course that explores the intersection between language and heatlh. Through research papers, we will gain a better understanding of how language plays a pivotal role in both assessing health conditions and effectively conveying vital health information. Throughout the course, students will delve into the various dimensions of language (spoken speech, written text, sociolinguistic features of non-standard varieties) and its implications for individual and public health.
How can we analyze and describe the structure of English? Maybe you have already looked at more than one of the big reference grammars of English, have compared them with a (considerably smaller!) standard school grammar, and have been puzzled by the variety of different terms, concepts and theoretical assumptions you found. This course is designed as an introduction to basic problems in the description of the morpho-syntactic structure of English. Apart from learning the basics of English morpho-syntactic structure, you will have the opportunity to practice the art of working with large reference grammars and relate the terminology you find there to the linguistic principles underlying such descriptions. We will start by looking at what proper or correct English is and how the notion of grammar can be applied to different varieties of English. We will then move on to look at word structure and clause structure of English.
This course provides you with an elementary introduction to English phonetics and phonology, designed for those who have no previous knowledge whatsoever of the subject. It begins with a very elementary introduction to articulatory phonetics, and then proceeds to introduce the student to a very simplified account of some of the main aspects of the phonological structure of present-day English. Languages other than English will also be examined to compare and contrast the linguistic structural differences and gain insights on linguistic generalisation.
Is technology really as innocent and as objective as they are said to be? As machine learning (ML) and Artificial Intelligence (AI) becomes more prominent in our life from speech and voice recognition by Alexa to automatic fake news warnings of social media posts, issues with social bias and fairness in language technology become more pertinent than ever before. Negative impacts that biased ML and AI could have for various social identities such as race, gender and culture. We first introduce the concept of bias in language technology, and the different types of biases such as racial, gender, cultural biases. To begin to understand the cause of these biases, we will cover the basic underlying structure of some of the technologies such as Automatic Speech Recognition, hate speech detection and word association. To evaluate these biases, we will learn to generate test cases that can be used to evaluate trained systems, and the metrics that are used for measuring bias/fairness. Finally, we will cover the basics of bias mediation and techniques.
This colloquium is for all students who want to discuss their project for a Bachelor, Master or doctoral thesis and who wish to receive feedback and support. The colloqium takes place every second week in person. The other weeks you would be required to work as a group. We will use the first session to decide on the topics of presentation, which will then have to become a part of the colloquium`s program. In the in-person weeks, we will also cover research related skills, such as time-management, hypothesis generation, critical reading and more.
Have you ever wondered why we (humans) are really good at changing words? Like, if there`s more than one cat, we just add an -s to make it "cats". But, when we see more than one child, we make it "children". How do we know which pattern to follow? In this course, we will explore how humans learn these word changes. Specifically, we will look into how humans express a wide range of meanings and relationships without inventing new words (i.e we are looking at inflection). We will start by looking at prominent theories that help us understand how both children and adults acquire this knowledge of inflection. We will also engage broadly with the computational modeling approaches that help us better understand the complex process of language acquisition. As part of the course requirements, you are not required to do any programming.The course involves reading and understanding current research papers in the field of child and adult language acquisition, computational morphology, and phonology (mainly, SIGMORPHON (https://sigmorphon.github.io/) papers).
It is as necessary to be numerate as it is to be literate, but students in the field of humanities are often not as numerate as they are literate. They will need to evaluate evidence that are based on probability-based models or statistical results in many of the courses that they take in university, as they consider the efficacy of vaccination and the severity of the pandemic, as they begin to vote in local and national elections, as they search for employment on the job market after graduating, and so on. With an increasingly digital world filled with big data, a command of statistical reasoning is more important than ever. In this course, we will learn numeracy through linguistics, specifically through phonetics and phonology by learning to analyse the sounds of languages quantitatively. How do we analyse the sounds of languages quantitatively? This course, Analysing the sounds of languages, covers the basics of quantitative methods using real data taken from the field of phonetics and phonology. We will provide a gentle introduction to the statistical program R (www.r-project.org) -- a program that is used by data scientists in the tech. industry and academic researchers. The course will consist of a combination of lectures, and plenty of hands-on exercises. We introduce research questions, such as “Do Southerners in the US really talk more slowly?” or “Why do we expect scholarly words to be longer than familiar words?” as a framework for introducing the numerical concepts required to answer research questions such as these. In this course, statistical methods are introduced with a research question and a solid understanding of the data, which is why we use real data and questions that are relevant to anyone who commands a spoken language. A good amount of space is also devoted to illustrating how to formulate and answer a research question, and hypothesis development and testing.
Have you ever been curious about why Voice Assistants (Siri, Amazon Echo and Google Assistant) sometimes struggle to understand your English accent? As linguists, we can play a crucial role in evaluating these sophisticated systems. In this class, you will assess the performance of Automatic Speech Recognition systems (ASR) by evaluating them against your own recorded speech and other existing speech recordings. You will learn how to use recording equipment in a laboratory setting as well as how to cut and prepare audio for further processing.