Language attrition is the gradual loss of a language due to reduced use, without any pathology involved. It cannot be understood without making clear concepts like L1, Mother tongue, L2, FL, and Heritage languages among others. Are all kind of attrition the same? Are attrition and bilingualism always related? Linguistic and extralinguistic factors, how to 'measure' and study them will be address and also used for analysing our data.
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.
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.
This is the second half of the two-semester introduction to linguistics. This semester, we will turn to the analysis of meaning and language in use, including topics such as semantics, pragmatics, historical linguistics, sociolinguistics and linguistics as an empirical science.
Why does your voice sound different on a recording? How can we tell speakers apart just by listening? What makes vowels sound different from each other? In this course, you will learn to see what you hear. Using Praat, a software that lets you visualize and measure speech, you will explore the acoustic properties of speech.
Taught by a team of three instructors from the areas of linguistics (Professor Dr. Kevin Tang), medicine (Professor Dr. Esther Florin), and music (Dr. Carter Williams), this course will embrace an interdisciplinary approach to digital signal processing that will allow student to explore applications in medicine, linguistic, and creative fields.
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.