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Language in social communication_Language UX in interaction with voice assistants and chatbots

General data

Course ID: 3201-LST-OC-LSC1
Erasmus code / ISCED: (unknown) / (unknown)
Course title: Language in social communication_Language UX in interaction with voice assistants and chatbots
Name in Polish: Optional courses: language in social communication_Language in Voice User Interfaces
Organizational unit: Institute of Applied Linguistics
Course groups:
ECTS credit allocation (and other scores): 3.00 Basic information on ECTS credits allocation principles:
  • the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS;
  • the student’s weekly hourly workload is 45 h;
  • 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes;
  • weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS;
  • work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load.
Language: (unknown)
Type of course:

elective courses

Mode:

Classroom

Short description:

The aim of this course is to introduce basic and more in-depth (depending on group’s background and needs) knowledge on Language and Speech Technologies as part of Natural Language Processing. Students will also learn about culture- and language-based product and market choices made during voice interfaces development. They will be introduced to the impact of language variation (standard, dialects, vernacular, multilinguality) on development and product decisions.

We will also discuss the topic of Accessibility in human-device interaction for users with vision or hearing impairments. An important part of this course is also learning how to identify and develop linguistic and computational skills relevant for speech technologies development. Students will receive a well-balanced mix of theoretical background and practical knowledge.

Full description:

The aim of this course is to introduce basic and more in-depth (depending on group’s background and needs) knowledge on Language and Speech Technologies as part of Natural Language Processing. Such technologies are present in many common appliances and devices (e.g. smartphones, TV, digital appliances) used by a majority of people in the world . Attendees will find out how specific modules in various speech & text language interfaces work and how they, as linguists, can contribute to developing software for Speech Technologies.

Students will learn about culture- and language-based product and market choices made during voice interfaces development. They will be introduced to the impact of vertical and horizontal language variation (standard, dialects, vernacular, multilinguality) on development and product decisions.

We will also discuss the topic of Accessibility in human-device interaction for users with vision or hearing impairments and how one can secure inclusive user interaction available to all diverse groups of customers.

An important part of this course is also learning how to identify and develop linguistic and computational skills that can lead to participating in state of the art projects in contemporary language AI development, including Large Language Models training and evaluation.

The students will receive a well-balanced mix of theoretical background and practical knowledge based on hands-on experience of the lecturer as a linguist, project coordinator and product manager in Speech & LanguageTechnologies in Research & Development area of one of the largest global technology companies.

At the end of this course it will not be a mystery anymore how “talking to a phone” in Voice Assistants and other Voice Interfaces actually works.

The course will be conducted using accessible language and information-sharing that does not require prior knowledge of the domain, but also with many opportunities to expand knowledge if a student already has prior theoretical or practical experience with the subject.

Students will have a chance to develop unique skills combining sociolinguistics, computational linguistics, user- and product-oriented approach. Through open discussions, group tasks and ideas exchange, they will be able to peek into the world of language AI and the role they can play in contributing to it.

Here are a few examples of workshop-type learning included in this course:

● Group tasks: product- and user-oriented solution seeking for speech technology linguistic issues,

● Interactive brainstorming to gather and categorize ideas,

● Testing voice interaction on devices (smartphones) to work out problem solutions and improvement ideas.

Student’s contribution to the course:

● 30h - participation in classes

● 15h - readings and source analysis, individual and group assignments

Learning outcomes:

Knowledge

K2_W02 in-depth, biological, cultural and communicative-social aspects of language use

K2_W04 in-depth, fundamental problems of language use as an interlingual and intercultural phenomenon

K2_W08 in-depth, the role of language in communication between people and cultures, and linguistic phenomena in a broader cognitive, communicative and social context

K2_W05 in-depth, the main directions of development and contemporary research trends in linguistics (theoretical, computational, cognitive, corpus, social/text linguistics) and knows where the most important linguistic research centers in Europe and the world are located

Skills

K2_U01 use in-depth theoretical and practical knowledge to carry out research work and solve complex problems in linguistics (theoretical, computational, cognitive, corpus, social/text linguistics) using appropriate methodology

K2_U03 use advanced research tools of linguistics (theoretical, computational, cognitive, corpus-based) and select research methods appropriately to the problems undertaken

K2_U04 use in-depth knowledge of linguistics (theoretical, computational, cognitive, corpus-based, social/text linguistics) through the selection and appropriate application of modern information and communication technology (including statistical, corpus, eye-tracking and EEG analysis software) when working with research data

K2_U08 communicate in an understandable way, including with non-specialists, on topics related to linguistics (theoretical, computational, cognitive, corpus, social/text linguistics) and adequately justify the decisions made and language strategies used

K2_U11 lead the work of a team in a linguistics project using advanced research methods and new technologies

K2_U12 independently acquire knowledge in the field of linguistics (theoretical, computational, cognitive, corpus, social/text linguistics) and evaluate the usefulness of the learned methods, practices and procedures in their own professional activity

Social competences

K2_K02 recognize the importance of linguistic knowledge in solving cognitive and practical problems and to consult with experts

K2_K03 adequately identify and resolve problems of interlingual, intercultural and social communication

K2_K05 think and act in an entrepreneurial manner within the framework of ongoing linguistic projects, as well as individual activity in the domestic and international markets

K2_K06 perform the profession of a language, cultural, educational mediator in accordance with the principles of professional ethics

K2_K08 perform the professional role of a linguist responsibly and with an entrepreneurial spirit, taking into account changing social and market needs

Assessment methods and assessment criteria:

Attendance, active participation and group oral exam

Classes in period "Summer semester 2023/24" (in progress)

Time span: 2024-02-19 - 2024-06-16
Selected timetable range:
Navigate to timetable
Type of class:
Seminar, 30 hours, 10 places more information
Coordinators: Magdalena Hirna Budka
Group instructors: Magdalena Hirna Budka
Students list: (inaccessible to you)
Examination: Course - Grading
Seminar - Examination
Course descriptions are protected by copyright.
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