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.
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.
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.
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.
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.
Recent advances in both computing power and statistical thinking have allowed the use of huge amounts of data in a way not feasible in earlier times. In this course, we will learn how to use these new methods and data sources to investigate the structure of language. Of course, language is a multimodal phenomenon, i.e., it exists not just in the form of written text, but also in spoken form, and these different modes require different approaches. We will learn about the different methods needed to approach these different modalities of language. In learning about these statistical applications, we will be making use of the commonly used R programming language. Previous knowledge of R would of course make things easier, but is not a prerequisite for participation. Potential students who are very apprehensive about programming may also want to consider the parallel course (with the same title of Corpus Linguistics), taught by my colleague Ghattas Eid, which will have less of a computational focus.
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. By the end of the course, you will learn how to perform i) pre-processing of text files (cleaning up raw text files), ii) automatic linguistic annotation, such as Part of Speech tagging (automatically adding labels such as Noun, Adjective to each word), Name Entity Recognition (identifying proper names, time, date, places, events) and Sentiment (fear, anger, happy, surprise…) iii) the basics of classifying documents, authors and sentiment. Students will get insight into how these systems work (and why it is still so difficult to do natural language processing well). We also consider social and ethical considerations such as privacy, job creation and loss due to language technologies, and the nature of consciousness and machine intelligence.
This course aims to fill a gap between the students’ knowledge in phonetics and phonology and their ability to applying that knowledge to ask non-trival research questions using a large amount of speech and lexical data. It would cover corpus compilation, semi-automatic annotation (phonetic transcription and forced-alignment), extraction of phonetic and phonological variables and the basics of statistical analyses of corpus data. It complements other courses such as advanced phonetics, quantitative and experimental methods, and corpus/computational linguistics. The course will involve the use of programming languages (such as Python, R and unix commands) and they will be introduced as needed. While we won't be using a single textbook, we will likely sample from the following textbook: Harrington, J. (2010). Phonetic analysis of speech corpora. John Wiley & Sons.
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 collaboratively to design the project, collect data, analyze the data, and interpret results. Coronavirus guidelines permitting, this course will take place entirely in-person.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 results Following the collaborative BN course, each student will write their own paper for the AP component of the Methodenmodul. All stages of the research and writing will be supported. The goal is for students to learn these skills in the course. For this reason, no background in phonetics, phonology, or statistics is assumed (other than the Basismodul).
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.