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. Using mini-portable computers, NVIDIA® Jetson Nano Developer Kit, you will build your own text-to-speech system that can synthesize written text into spoken language. Prior knowledge of programming or other technical skills is not required. In this course, you will acquire new digital skills that complement your linguistic training. Specifically, you will learn about: practically applying your Phonetics knowledge, the role of Linguistics in text-to-speech systems, the components of Text-to-speech systems, building your own Text-to-speech system
This advanced seminar will explore the relationship between two closely-linked linguistic fields of phonetics (the study of language sounds) and phonology (the study of sound patterns). In what ways do the methods and findings of phonetics and phonology overlap, contradict, or inform what another? Students will learn to engage with the material as researchers. We will practice how to read primary research articles, discuss ideas orally and in writing, and conduct original research. Students are encouraged to explore their own interests, and parts of the syllabus will change depending on the interests of the group. The final research paper is an opportunity for each student to more deeply explore a topic of their interest in, or relating to, phonetics-phonology. The development of the paper topic will take place in dialogue with the readings and each other, with structured guidance and feedback.
You do not have to be a computer wizard to break into the language technology industry. Computational models of human language (Natural Language Processing) are only as good as the annotations of different linguistic structures. Given the richness of human language, high quality and complex annotations can only be performed by humans equipped with formal linguistic training, native speaker's intuition, and knowledge of the world. Linguistic data annotation is thus extremely important, making it a sought-after skill in the language technology industry. 'Data annotator' is an entry-level position at technology companies which requires linguistics training but not programming experience. Annotators work in an interdisciplinary environment with engineers, managers, linguists and so on, and can find opportunities for furthering their careers in the technology industry. This course offers a taste of annotation work for those curious about the field, and provides practical training and experience for applying for such a position. In this course, students would gain a basic understanding of the annotation process, learn about the creation of different annotation schemes, work with annotation softwares commonly used in the industry and evaluation of annotations. Along the way, students will gain familiarity with common text-processing tools and data formats.