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.
The ability to use digital tools is increasingly valuable to students in all fields, including the humanities. This course is intended for students with no programming background whatsoever who are interested in taking the first steps towards writing industry-grade software. We’ll begin by exploring computer architecture and move on to understand how programs work behind the scenes by writing simple and useful programs. These skills will allow students to think like a Computer Programmer. Participants will gain familiarity with the Unix command line along with a Code editor (Vim). The language used for the course will be Python because of its beginner-friendly syntax. Basics of Databases, Networking and Cloud computing will also be emphasized. After taking this course, students will become familiar with general concepts in computer science, gain an understanding of the general concepts of programming, and obtain a solid foundation in the use of Python. There is no specific textbook for this course. Learning resources consist of articles and chapters available online.
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.
Students will work together to design, conduct, and interpret an original experimental study. The particular study will be developed by the class, but will involve acoustic analysis of probabilistic phonetic reduction. The course will be structured as a research project with the following components: (1) Motivation: students will read several papers around a single topic (phonetic reduction) in order to frame the research project. (2) Predictions: working in groups, students will formulate one or more sets of predictions. (3) Experimentation: working in groups, we will design and conduct one or more experiments. (4) Analysis and Interpretation: we will interpret the results in light of the predictions. Coronavirus guidelines permitting, students will use equipment in the new Computational Phonetics lab in order to conduct experiments. Students should expect to work in collaboration with classmates, and active participation in every stage of the course is required for BN credit. Students interested in writing a paper for an AP can use the class project as the basis for their own project.
In this course we will be discussing the basic notions, terminology and methodology of modern linguistics. We will focus on core areas of English linguistics. In this first part of the Introduction to English language and linguistics we will deal with the structure of language (in particular of the English language) and acquire the terminology and methodology of modern linguistics. The focus will be on the core areas of linguistics: the study of sound structure (phonology), word structure (morphology), and sentence structure (syntax). In the second part of the Introduction to English language and linguistics, the formal levels of linguistic analysis (phonology, morphology, syntax) will be viewed in relation to their meaning(s) as well as to their contexts of use. Topics therefore include semantics, pragmatics, and sociolinguistics.
This is the second half of the two-semester introduction to linguistics. In this semester we will turn to the analysis of meaning and language use, including topics such as semantics, pragmatics, historical linguistics and sociolinguistics.
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.
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. Throughout the course, students will work collect data, analyze the data, and interpret results. By the end of the course, students will:- gain experience working together on a complex project- formulate a hypothesis and empirical predictions- design and implement an experimental protocol- analyze data using appropriate software, e.g. Praat, R- visualize data- interpret the hypothesis in light of the resultsStudents will finish the course with a proposal that can be developed into an AP paper if they so choose. After the class period, students will have the option to meet regularly with each other and with the instructor as they write their papers.
Students will develop an understanding of the history and current status of the languages of the United States. They will use linguistic data and structure to inform study of language variation, history, contact, endangerment, and revitalization.
Have you ever wondered why Voice Assistants (Siri, Amazon Echo and Google Assistant) could not quite understand your English accent? We, as linguists, can play an important role as evaluators of such complex systems. Through this beginner-friendly course, you will open up the black box of language technology by building them with mini-portable computers. In the process, you will acquire new digital skills that complement your linguistic training. Specifically, you will be given the unique opportunity to apply your English and linguistic knowledge for building everyday language technology applications such as evaluating the voice assistant's ability to perceive and produce different English accents, prosody patterns, styles, and emotions. You will be primarily working with mini-portable computers, [NVIDIA® Jetson Nano Developer Kit](https://developer.nvidia.com/embedded/jetson-nano-developer-kit). With the NVIDIA Kits, you will build an interactive machine that can speak (Speech Synthess - convert written text into spoken speech) and can listen (Speech Recognition - transcribe spoken speech into written text). Furthermore, you will evaluate automated systems using linguistic analysis and provide you an opportunity to come up with novel linguistically-motivated evaluation methods. Prior programming knowledge is NOT required. You would be provided with instructions on developing these technologies and basic programming knowledge will be introduced as needed. Throughout the course, the focus will be on whether these language technologies can learn human-like linguistic abilities. At the end, you would be equipped to build your own interactive Speech Synthesizer and Speech Recognition systems with the NVIDIA devices.e/Software interaction. These digital skills are the most sought-after ones in the language technology industry.