Einleitung
Der Modulkatalog hilft Ihnen bei der Planung Ihres Studiums, indem er Ihnen
eine Übersicht über alle Module Ihres Studienprogramms bietet.
Das Dokument enthält folgende Rubriken:
Der Modulkatalog ist ein Informationsdokument und nicht rechtsverbindlich.
Zu Beginn jedes Semesters wird eine aktuelle Version auf der Website der
Philosophischen Fakultät publiziert.
Übersicht über die Modulgruppen
Übersicht über die Module in den Modulgruppen
06M-7526i01Wissenschaftliche Vertiefung
06M-7526i02Kernbereich Digitale Linguistik
06M-7526i03Praxis der Digitalen Linguistik
Katalog der Pflichtmodule, Wahlpflichtmodule und Wahlmodule
Der Katalog enthält Informationen zu jedem Pflicht- und Wahlpflichtmodul.
Zum Teil finden Sie auch Informationen zu Wahlmodulen (Modultitel in eckigen
Klammern). Beachten Sie, dass die Titel von Wahlmodulen semesterweise wechseln
können und dass oft weitere, nicht im Modulkatalog enthaltene Wahlmodule
angeboten werden. Diese und alle anderen semesterbezogenen Informationen
(wie Veranstaltungstitel, Termine, Dozierende, Informationen zur Buchung)
entnehmen Sie dem aktuellen Vorlesungsverzeichnis.
06SM523-101 Introduction to Experimental Research
Moduldetails: 06SM523-101 Introduction to Experimental Research
| Modulgruppe |
Wissenschaftliche Vertiefung |
| Modultyp |
Wahlpflicht |
| ECTS |
3 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module introduces the process of designing and administering experimental research studies in linguistics and language technology. It covers the formulation of research questions and hypotheses, experimental design, the developlemt of tasks and stimulus materials, and key considerations for participant recruitment. The module also introduces a range of methodologies used to collect linguistic data in different modalities, with a special focus on the linguistic lab infrastructure available at UZH. Finally, the module addresses the administration of studies as well as the postprocessing and interpretation of empirical data. It provides an early foundation for the research cycle and supports later coursework on the modeling of experimental data, scientific writing and ethical conduct. |
| Lernziel |
This module introduces the process of designing and administering experimental research studies in linguistics and language technology. It covers the formulation of research questions and hypotheses, experimental design, the developlemt of tasks and stimulus materials, and key considerations for participant recruitment. The module also introduces a range of methodologies used to collect linguistic data in different modalities, with a special focus on the linguistic lab infrastructure available at UZH. Finally, the module addresses the administration of studies as well as the postprocessing and interpretation of empirical data. It provides an early foundation for the research cycle and supports later coursework on the modeling of experimental data, scientific writing and ethical conduct. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
None.
The module is complemented by the module "Scientific Writing and Ethical Conduct" offered in a later semester that deals with the subsequent stages of the research process, specifically, writing up the research results and publishing data, models, and code. |
| Leistungsnachweis |
Portfolio |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-s21 [Seminar]
Moduldetails: 06SM523-s21 [Seminar]
| Modulgruppe |
Wissenschaftliche Vertiefung |
| Modultyp |
Wahl |
| ECTS |
6 |
| Lehrform |
Seminar |
| Allgemeine Beschreibung |
This module provides in-depth engagement with a specific topic in language technology. Students learn scientific working methods, including analyzing research literature, interpreting empirical results, and evaluating theoretical approaches. They prepare and deliver a scientific presentation and write a paper expanding on their topic. |
| Lernziel |
Students can:
1. gain insight into a specific area of language technology.
2. acquire methodological skills for scientific research.
3. present complex topics clearly.
4. write a scientific paper." |
| Unterrichtssprache |
siehe Vorlesungsverzeichnis |
| Voraussetzungen |
keine |
| Leistungsnachweis |
Written paper and presentation |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
keine Wiederholungsmöglichkeit |
| Angebotsmuster |
1-semestrig (einmalig) |
| Organisation |
Institut für Computerlinguistik |
06SM271-516 Quantitative Methods
Moduldetails: 06SM271-516 Quantitative Methods
| Modulgruppe |
Kernbereich Digitale Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This course introduces the basic concepts of statistical analysis as used in modern linguistics, covering data description and visualization as well as basic techniques of machine learning and modelling. The course also introduces the basic concepts of frequentist vs Bayesian approaches and the use of simulations and baseline models. |
| Lernziel |
Students are familiar with the basic concepts and methods of statistical analyses of linguistic data and are able to perform such analyses themselves |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
Notice: the following knowledge of high school mathematics is required and has to be solid:
- Concept of spaces / number systems (e.g., natural, rational and real numbers);
- Basic Functions: Linear, polynomial, exponential, logarithmic function;
- Differential Calculus: Extreme values, derivatives, integrals;
- Linear Algebra: Vectors, vector spaces, linear transformations, matrices, dot (scalar) product;
- Probability Theory: Random variables, probability distributions (uniform, binomial, normal, exponential), joint and marginal distributions. |
| Leistungsnachweis |
Portfolio (80% written exam and 20% written exercises). All elements of this portfolio must be completed. If an element is not completed, the module is considered as «failed». |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Linguistik Zentrum Zürich |
06SM271-517 Language Data Acquisition
Moduldetails: 06SM271-517 Language Data Acquisition
| Modulgruppe |
Kernbereich Digitale Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
9 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This course introduces methods and techniques of linguistic data acquisition and consists of the following parts: Audiovisual techniques of data acquisition, metadata management, transcription, corpus design and corpus building, conversions (e.g. OCR), experiments (including field experiments), basic qualitative methods ethical and legal issues |
| Lernziel |
Students are familiar with the core methods and techniques of data collection both in experimental and naturalistic settings: They know how to design and carry out experiments, are familiar with the use of video and audio recording devices and editing tools, and know how to design and build up a corpus. They have a basic understanding of the constraints on data acquisition for both qualitative and quantitative purposes and are familiar with ethical and legal issue of data. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
none |
| Leistungsnachweis |
Portfolio (80% written exam and 20% proof of self-study achievements). All elements of this portfolio must be completed. If an element is not completed, the module is considered as «failed». |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Linguistik Zentrum Zürich |
06SM271-518 Language Data Processing
Moduldetails: 06SM271-518 Language Data Processing
| Modulgruppe |
Kernbereich Digitale Linguistik |
| Modultyp |
Pflicht |
| ECTS |
15 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This 2-course-module introduces automatic corpus annotation ("Introduction to Language Data Processing") and programming ("Programming for Linguists") and consists of the following parts: Annotation, manipulation and extraction of linguistic data, basic skills in Natural Language Processing on various linguistic levels (morphology, syntax, semantics), basic Unix commands for text handling, regular expressions for pattern matching, file formats and markup languages, encoding and compression, programming in a modern scripting language (e.g. R or Python), introduction to linguistic databases. |
| Lernziel |
Students get to know the core methods and tools for automatic corpus analysis, annotation and evaluation. They learn about cross-language alignment and gain insights into the advantages of parallel corpora. Students learn how to use Unix language processing tools and obtain programming knowledge in a modern scripting language (e.g. R or Python) with a focus on the processing of linguistic data. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
none |
| Leistungsnachweis |
Portfolio (40% written exam for Introduction to Language Data Processing, 40% written exam for Programming for Linguists, 20% proof of self-study achievements in both courses). All elements of this portfolio must be completed. If an element is not completed, the module is considered as «failed». |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Linguistik Zentrum Zürich |
06SM523-003 Mathematical Foundations for Language Technology 1
Moduldetails: 06SM523-003 Mathematical Foundations for Language Technology 1
| Modulgruppe |
Kernbereich Digitale Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module reviews and strengthens the mathematical foundations required for understanding and developing methods in language technology. It covers essential concepts from logic, set theory, probability theory, descriptive statistics, combinatorics, analysis, linear algebra, and information theory, and highlights how these areas underpin core techniques in computational linguistics. The module introduces practical exercises to build mathematical intuition and to support the implementation and analysis of language technology systems. Students also work with computational tools to explore, analyze, and visualize data. |
| Lernziel |
Students can:
1. explain language technology methods using mathematical concepts from the covered areas.
2. use mathematical tools to design solutions to selected problems in language technology.
3. analyze and visualize data using computational methods. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
None. |
| Leistungsnachweis |
Portfolio: 75% final exam, 25% mid-term exam |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-004 Machine Learning for Language Technology
Moduldetails: 06SM523-004 Machine Learning for Language Technology
| Modulgruppe |
Kernbereich Digitale Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module introduces the fundamental concepts and methods of machine learning as they apply to language technology. It covers both theoretical foundations and practical exercises, with particular emphasis on deep learning and neural network architectures. The module presents logistic regression, multilayer perceptrons, recurrent neural networks, and Transformers. Students implement basic architectures and apply machine learning techniques to selected tasks in language technology. |
| Lernziel |
Students can:
1. explain key concepts in machine learning.
2. compare different machine learning approaches including logistic regression, MLPs, RNNs, and Transformers.
3. implement basic machine learning architectures.
4. design solutions to selected language technology problems using machine learning. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
Successfully completed module "Mathematical Foundations for Language Technology 1" or equivalent knowledge. |
| Leistungsnachweis |
Portfolio: 80% final exam, 20% exercises |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Frühjahrssemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-005 Programming in Language Technology 2
Moduldetails: 06SM523-005 Programming in Language Technology 2
| Modulgruppe |
Kernbereich Digitale Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module deepens programming skills in Python with a focus on developing software for language technology applications. It emphasizes writing clear and maintainable code, applying modern programming techniques to domain-specific tasks, and using essential practices in code management such as version control, testing, debugging, and systematic code review. Integrated exercises support the refinement and evaluation of software in natural language processing contexts. |
| Lernziel |
Students can:
1. apply modern programming knowledge and skills to solve tasks in language technology.
2. review, debug, and improve human- and machine-written code in language technology applications.
3. use essential code management practices, including version control and testing, to support systematic software development. |
| Unterrichtssprache |
Deutsch und/oder Englisch |
| Voraussetzungen |
Successfully completed module "Programming in Language Technology 1" or equivalent knowledge. Knowledge to the extent of "Introduction to Language Technology". |
| Leistungsnachweis |
Portfolio: 75% final exam, 25% exercises |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Frühjahrssemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-111 Fundamentals of Large Language Models
Moduldetails: 06SM523-111 Fundamentals of Large Language Models
| Modulgruppe |
Kernbereich Digitale Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module introduces the fundamental ideas underlying large language models (LLMs) and their importance in research, industry, and language technology. It covers core concepts such as training objectives and model architectures and examines techniques that enhance the problem-solving abilities of LLMs, including reasoning and tool use. The module also discusses engineering methods that enable LLMs to scale to large datasets and parameter counts. |
| Lernziel |
Students can:
1. explain how LLMs work and how they are developed.
2. apply LLMs to selected language technology tasks.
3. evaluate LLM performance systematically.
4. discuss the state of the art in LLM research and applications. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
Successfully completed module "Machine Learning for Language Technology" or equivalent knowledge. |
| Leistungsnachweis |
Portfolio |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-112 Language Technology with Multilingual and Multimodal Data
Moduldetails: 06SM523-112 Language Technology with Multilingual and Multimodal Data
| Modulgruppe |
Kernbereich Digitale Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module introduces key methods for multilingual and multimodal modeling in language technology. It examines longstanding tasks such as transforming text between languages in machine translation and converting audio recordings into text in speech recognition, and shows how multilingual and multimodal approaches can be beneficial even for tasks confined to a single language or modality, particularly in low-resource settings. The module discusses methods developed for mapping between languages and modalities and explains how shared internal representations support cross-lingual and cross-modal transfer. In addition, students analyze the practical consequences of these approaches, including positive transfer effects as well as undesirable biases that can arise from multilingual or multimodal systems. |
| Lernziel |
Students can:
1. build multilingual and multimodal language technology applications.
2. explain common methods for mapping between languages and modalities, such as those used in machine translation and related tasks.
3. describe how shared internal representations enable cross-lingual and cross-modal transfer.
4. analyze benefits and limitations of multilingual and multimodal modeling, including transfer effects and biases. |
| Unterrichtssprache |
Deutsch und/oder Englisch |
| Voraussetzungen |
Successfully completed modules "Machine Learning for Language Technology" and "Programming in Language Technology" or equivalent knowledge. |
| Leistungsnachweis |
Portfolio |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Frühjahrssemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-114 Scientific Writing and Ethical Conduct
Moduldetails: 06SM523-114 Scientific Writing and Ethical Conduct
| Modulgruppe |
Kernbereich Digitale Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
3 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module introduces students to research ethics and data protection in the context of sharing and publishing data, models, and code. It also covers conventions of scientific writing, focusing on research in language and speech technology. Topics include preparing datasets, models, and code for open research, literature management, and the writing of scientific texts such as theses and conference papers. The module also addresses responsible use of generative AI in scientific writing. |
| Lernziel |
Students can:
1. identify important aspects of data, model, and code sharing.
2. write scientific texts that follow common conventions and use generative AI responsibly.
3. communicate research outcomes clearly and accessibly. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
None.
The best time to attend this module is following the completion of a seminar or programming project and before starting the bachelor's thesis. In that case, the seminar or programming project and a potential write-up can serve as a starting point for the tasks of this module. The module can also be attended without this prior work.
Prior attendance of the module "Introduction to Experimental Research" is recommended. |
| Leistungsnachweis |
Portfolio |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-115 Software Lab
Moduldetails: 06SM523-115 Software Lab
| Modulgruppe |
Kernbereich Digitale Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This module treats software development as a collaborative team process. It focuses on the development of language technology applications using a combination of technologies, including web interfaces, AI models, databases, and data visualizations. A special focus is placed on the creative process: collaborating effectively with team members, turning an initial idea into a working prototype, and presenting the result to an audience. |
| Lernziel |
Students can:
1. collaborate in a small team to design and implement a software project in language technology.
2. demonstrate a prototype to an audience.
3. document the project in a written report and reflect on the creative process.
4. provide constructive, actionable feedback to peers.
5. independently acquire technical skills needed for their project, such as software development tools, web technologies, and data modelling. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
Successfully completed modules "Programming in Language Technology 1" and "2" or equivalent knowledge. |
| Leistungsnachweis |
Portfolio |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-519 Fundamentals of speech sciences and signal processing
Moduldetails: 06SM523-519 Fundamentals of speech sciences and signal processing
| Modulgruppe |
Kernbereich Digitale Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Vorlesung |
| Allgemeine Beschreibung |
Experience the captivating world of speech signal processing. Discover the essential techniques that enable us to decode, manipulate, and reproduce the human communication with speech. Learn about signal and system theory necessary for speech processing in both human interaction and cutting-edge technological applications. This lecture series will equip you with the fundamental knowledge needed to unravel the intricacies of speech communication and embrace the possibilities it holds. |
| Lernziel |
(1) Fundamental skills in speech signal processing (2) Understanding of speech acoustics like signal types, signal transformations, acoustic systems, signal and system theory (3) Application of the signal processing techniques in research and industrial products. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
An interest in speech signal processing with computers is required. |
| Leistungsnachweis |
Portfolio: (a) weekly assignments, 40% (b) end of term exam, 60% |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Frühjahrssemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-520 Instrumental techniques of phonetic research
Moduldetails: 06SM523-520 Instrumental techniques of phonetic research
| Modulgruppe |
Kernbereich Digitale Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Übung |
| Allgemeine Beschreibung |
Since speech is a transient event, phoneticians regularly resort to the aid of technical devices in order to record, describe and analyse the production, the acoustics and the perception of speech sounds. Hence, in this module we look at the technical side of phonetic research and the students acquire and develop skills and techniques necessary for the successful deployment of such devices, ranging from sound recording equipment (especially recorders and microphones) to more specialized phonetic equipment (such as the laryngograph) to software solutions geared specifically towards the need of phoneticians (such as Praat or the R-package 'vowels'). |
| Lernziel |
Students know how to make high-quality audio recordings for phonetic research purposes. They can annotate sound files, make reliable measurements in them (formants, pitch, intensity, etc.) and produce meaningful visualizations (wave forms, spectra, spectrograms, etc.) with suitable software. They also understand how to read spectrograms so as to draw informed conclusions about the temporal and spectral characteristics of speech events. Moreover, students understand the most important key notions and concepts in automatizing measurements and in making them replicable (scripting). |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
Students are required to have attended an introductory module in phonetics at bachelor or master level. |
| Leistungsnachweis |
During the semester students run guided analyses on spoken material both as part of the course but also as personal homework. In addition students are recquired to hand in a small-scale empiric study (7-10 pages) to be handed in a fortnight after the last meeting of the semester. Both their analyses during the semester and their final report form their portfolio and thus the basis for the evaluation of their performance. |
| Notenskala |
bestanden/nicht bestanden |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Frühjahrssemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-529 Intermediate Methods and Programming in Digital Linguistics
Moduldetails: 06SM523-529 Intermediate Methods and Programming in Digital Linguistics
| Modulgruppe |
Kernbereich Digitale Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Tutorat, Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
This course is designed to refresh and to deepen programming skills in Unix and Python. We teach basic operators and functions, the handling of lists and dictionaries as well as the basics of object-oriented programming. It is particularly important that the students acquire the ability to prepare text and speech data for further processing.
Through practical tasks and exercises, we train the algorithmic and programming skills of the participants. |
| Lernziel |
Students will be able to use Unix-based systems and Unix language processing tools efficiently. Students will know the basic data types, control structures and functions of Python. Students will be able to design problem solutions and to implement them in Python. Students will know how to use basic tools and programming libraries for corpus linguistics. |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
Successful completion of the introductory course "Language Data Processing" of the Master Linguistics
This module is open only to Master's students. It may not be booked by Bachelor's students as a pre-Master's module. |
| Leistungsnachweis |
Portfolio |
| Notenskala |
1-6, in Halbschritten |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Frühjahrssemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-534 Introduction to Forensic Speech Sciences
Moduldetails: 06SM523-534 Introduction to Forensic Speech Sciences
| Modulgruppe |
Kernbereich Digitale Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Vorlesung mit integrierter Übung |
| Allgemeine Beschreibung |
Forensic Speech Science is a multidisciplinary field that applies various aspects of phonetics, linguistics, signal processing, and automatic speaker recognition for legal and investigative purposes. This module aims to introduce the goals, tasks (e.g. transcription, speaker comparison, disambiguation of disputed utterances) and practices of forensic speech and audio analysis. This module blends frontal teaching and hands-on sessions. |
| Lernziel |
By the end of this module, students will have achieved the following learning objectives: - A fundamental understanding of factors affecting the perception, analysis, and transcription of speech signals within investigative settings. - Develop familiarity with diverse methods for transcribing forensic audio materials, including using state-of-the-art automatic speech recognition systems. - Gain familiarity with multiple approaches to forensic voice comparison, including auditory assessment, acoustic-phonetic analysis, and automatic techniques. - Showcase their abilities through practical demonstrations in voice comparison and the transcription of forensic recordings |
| Unterrichtssprache |
Englisch |
| Voraussetzungen |
The participation to modules on Phonetics and Phonology is highly recommended. |
| Leistungsnachweis |
Portfolio: 50% assignments, 50% final course exam |
| Notenskala |
bestanden/nicht bestanden |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Herbstsemester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-510 Practical Training In-House
Moduldetails: 06SM523-510 Practical Training In-House
| Modulgruppe |
Praxis der Digitalen Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Praktikum |
| Allgemeine Beschreibung |
In this module, the students get in touch with scientific project work, that is, they learn how to do basic research. In order to accomplish these kind of skills, they read scientific literature, prepare and annotate data, apply statistical and machine learning methods to solve particular problems. They are also involved in the preparation of articles for workshops and conferences. The students work on a particular (partial) problem in a scientic context or even running project. This module can be booked to credit work done in a scientific project at the UZH. This module can be booked with 6 or 9 ECTS points. The amount of points will be decided in consultation with the module coordinator. |
| Lernziel |
The students (1) get in touch with research (2) read scientific literature (3) are involved in evaluation processes (4) take over particular tasks in the context of a project (5) are involved in the preparation of articles (6) get insights into practical work (7) deepen their knowledge and skills with respect to a particular topic |
| Unterrichtssprache |
Deutsch und/oder Englisch |
| Voraussetzungen |
This module cannot be booked by the students themselves, the booking has to be authorized by the module coordinator. There is no entitlement to this module, the module will only be offered if a suitable position is available in a project. The requirements will be defined according to the topic. |
| Leistungsnachweis |
documented practical work |
| Notenskala |
bestanden/nicht bestanden |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Semester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-512 Programming Project 1
Moduldetails: 06SM523-512 Programming Project 1
| Modulgruppe |
Praxis der Digitalen Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Sonstiges |
| Allgemeine Beschreibung |
Programming projects aim at the consolidation of programming and the acquisition of software engineering skills. Starting with a particular research question and relevant literature, they work on a solution, define milesstones, aquire and/or annotate data, implent a programm and evaluate it using appropriate data. This module can be booked to credit work done in a programming project. This module can be booked with 3, 6 or 9 ECTS points. The amount of points will be decided in consultation with the module coordinator. |
| Lernziel |
The students (1) autonomously design a project (2) realize the project plan (3) use existing tools (4) do software engineering (5) document their work according to standards (6) evaluate the results (7) use software repositories |
| Unterrichtssprache |
Deutsch und/oder Englisch |
| Voraussetzungen |
In the duration of a study level a maximum of two programming projects can be booked. This module can be booked to credit work done in a programming project. It cannot be booked by the students themselves, the booking has to be authorized by the module coordinator. Before a programming project is started, it is essential to get the permission of the module coordinator (per Email). The prerequisites will be set according to the topic. |
| Leistungsnachweis |
documented practical work |
| Notenskala |
bestanden/nicht bestanden |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Semester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-513 Student Teaching Assistant 1
Moduldetails: 06SM523-513 Student Teaching Assistant 1
| Modulgruppe |
Praxis der Digitalen Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Sonstiges |
| Allgemeine Beschreibung |
A student teaching assistance serves the acquisition of basic teaching skills. This requires a deeper insight of the contents of the associated lecture and the ability to prepare teaching material in order to help the students to better understand it. The task also involves the preparation and correction of exercises. This module can be booked to credit the conducting of exercises/tutorials. This module can be booked with 3 or 6 ECTS points. The amount of points will be decided in consultation with the module coordinator. |
| Lernziel |
The students (1) cope with computational linguistics content from a teaching perspective (2) learn to prepare computational linguistics content in a way tailored to a student's audience (3) learn to correct exercises and give appropriate feedback |
| Unterrichtssprache |
Deutsch und/oder Englisch |
| Voraussetzungen |
In the duration of a study level a maximum of two modules «Student Teaching Assistant» can be booked, whereby the two modules must differ in content (also to any previously completed student teaching assistant modules). This module is booked in order to receive credit for a first job as a student teaching assistant at master's level.
This module is an application module, the application has to be authorized by the module coordinator (per Email). The lecturers have to be included in the communication. The open positions for student teaching assistants are usually posted on the mailing list of the Institute of Computational Linguistics (cllist@ lists.ifi.uzh.ch) a few weeks before the semester starts. Students interested in conducting exercises/tutorials of a specific course can apply anytime for the position directly with the lecturer and the module coordinator. The module in question must have been passed successfully beforehand. |
| Leistungsnachweis |
documented practical work |
| Notenskala |
bestanden/nicht bestanden |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Semester) |
| Organisation |
Institut für Computerlinguistik |
06SM523-517 Programming Project 2
Moduldetails: 06SM523-517 Programming Project 2
| Modulgruppe |
Praxis der Digitalen Linguistik |
| Modultyp |
Wahlpflicht |
| ECTS |
6 |
| Lehrform |
Sonstiges |
| Allgemeine Beschreibung |
Programming projects aim at the consolidation of programming skills and the acquisition of software engineering skills. Starting with a particular research question and relevant literature, they work on a solution, define milestones, acquire and/or annotate data, implement a program and evaluate it using appropriate data. This module can be booked with 3, 6 or 9 ECTS points. The amount of points will be decided in consultation with the module coordinator. |
| Lernziel |
The students: - autonomously design a project; - realise the project plan; - use existing tools; - do software engineering; - documuent their work according to standards; - evalute the results; - use software repositories. |
| Unterrichtssprache |
Deutsch und/oder Englisch |
| Voraussetzungen |
In the duration of a study level a maximum of two programming projects can be booked. This module can be booked to credit work done in a second programming project. It cannot be booked by the students themselves, the booking has to be authorized by the module coordinator. Before a programming project is started, it is essential to get the permission of the module coordinator (per Email). The prerequisites will be set according to the topic. |
| Leistungsnachweis |
documented practical work |
| Notenskala |
bestanden/nicht bestanden |
| Repetierbarkeit |
einmal wiederholbar, erneut buchen |
| Angebotsmuster |
1-semestrig (jedes Semester) |
| Organisation |
Institut für Computerlinguistik |
Ende
