Have you ever wondered why the voice from Google Maps sounds so robotic? In this course, you will take a look inside the black box of language technology and learn how text-to-speech systems work.
This course will provide an introduction to modern linguistic theory, introducing the basic ideas of the field and the necessary terminology and methodology, with a focus on the core areas of English linguistics.
Natural Language Processing plays a big role in our digital lives. We will demystify some of these everyday tasks that involve natural language processing: such as spelling and grammar correction, document classification, dialogue systems, machine translation, and forensic linguistics. On the practical side, we will focus on applying off-the-shelf tools that are often used in computational modelling of language data. Armed with these skills, you will be able to model language data quantitatively and ask measurable research questions.
This is a seminar course that aims to provide you with both theoretical and applied skills in the area of laboratory phonetics and phonology. It is designed to enable you to learn the process of a speech production experiment from start to finish.
This colloquium is for students who are writing their term papers, BA/MA/PhD theses and need feedback on their ongoing research in the area of linguistics. In each meeting, we will conduct peer-reviewing, group discussions and the students will have the opportunities to give individual update and receive feedback on their work in progress. Specific skills will be covered ranging from finding a research topic to thesis writing.
Language and Health is a seminar course that explores the intersection between language and heatlh. This course is tailored for students with a passion for linguistics, healthcare, psychology, communication studies, and related fields. 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 explore the various dimensions of language (spoken speech, written text, sociolinguistic features of non-standard varieties) and its implications for individual and public health.
Brain waves, speech, and music are all phenomena that can be encoded in digital signals. On the most basic level, a digital signal is a numerical representation of a stream of data over time. Signal processing can also include multidimensional data arrays, such as videos or fMRIs (functional magnetic resonance imaging). The real power of digital signals is that they allow for flexible manipulation of these data in order to change the output (voice changing, audio processing/effects) or analyze the signal (spectral analysis, measuring loudness or noisiness, segmenting into distinct elements). Thanks to widely available computer and audio hardware combined with various software packages, it is possible to work with these techniques in real-time systems, which enable direct feedback for the user of the system. After establishing some basics of how these techniques are implemented, we will be focusing on building or reengineering our own practical systems used in medical diagnosis or linguistics, with the goal of presenting these systems as working demonstrations or interactive installations connected with an end of semester poster presentation. While we will cover theoretical concepts, this will be a hands-on course, where we will work to develop projects.
The goal of this seminar is to gain research skills and to become familiar with the writing and research process. We will be dealing with the general steps of the research process, with conducting research using the tools and institutions available at our university, as well as with formal aspects of academic writing such as citations, formatting, structure of argumentation, and plagiarism. As academic conventions differ between institutes and departments, this course focuses on linguistic research in particular, and will provide the skills that are necessary for your term papers and BA dissertation.
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 these voice assistants by evaluating them against your own recorded speech. We will start by using the recording lab to record your voice and create a dataset. We will then use the voice assistants over this dataset. Once we know the possible errors from these systems, we will find the source of the errors using phonological analysis.
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. Through research papers, we will gain a better understanding of the the ethics, fairness, bias-related challenges in Natural Language Processing. Throughout the course, students will gain an overview of the various types of Natural Language Processing models (e.g., Automatic Speech Recognition, Language Model, hate speech detection) and its implications for bias, diversity, Inclusion, Environmental and human costs, privacy and governance.