Intro to Voice Technology syllabus: Difference between revisions
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=== Assignment 1: Wiki page on the history of speech recognition === | === Assignment 1: Wiki page on the history of speech recognition === | ||
''' | === '''Assignment 2: Wiki page on the history of speech synthesis''' === | ||
=== Assignment 3: Wiki page === | |||
=== Talking clock === | |||
=== Talking clock presentation === | |||
=== In class activities and participation === | |||
There are multiple ways to participate in class aside from talking. Therefore participation will be assessed in an inclusive way taking into account your engagement in group/individual activities, your connections with guest speakers, any additional peer review activities, and the way in which you support the class overall. To those ends, I’ll take into account your self-assessment which you will deliver to me via a form. | |||
Revision as of 09:42, 29 August 2023
Introduction
In this course, we will explore the foundations of speech synthesis and recognition, delving into the interplay between technology and language.
Learning outcomes
Upon the successful completion of the course “Introduction to Voice Technology”, you will be able to:
- explain the history of voice technology.
- explain the basic elements of speech synthesis and recognition.
- identify data resources for voice technology applications and know where to find them.
- describe data management requirements for collecting and storing speech and speaker data.
- elaborate on the value and relative importance of data management, licensing and privacy issues concerning speech and speaker data.
- describe core aspects within speech production and feature extraction.
- discuss with peers how human factors and relevant aspects of context affect the interaction between humans and voice technology systems.
- describe how the user acceptance of a voice technology application can be investigated.
Course structure
The course runs for 8 weeks. Each week has 2 classes of 1 hour 45 minutes (with a 15 minute break in the middle).
Classes are on Tuesday and Wednesday, 13:15 -- 15:00.
Guest speakers
The following guest speakers will contribute to this course.
- Dr Laurent Besachier, Principal Scientist and NLP Group Lead at Naver Labs (EU). Topics of interest
- Dr. Loredana Cerrato, Project Manager Nuance - Microsoft. See blog post.
- Dr Leigh Clark, Senior UX Researcher - Bold Insight UK
- Dr Jide Edu, Security Researcher at the Alan Turing Institute (London, UK)
- Dr Frederic Robinson, Founder of LeapTech (Basel, Switzerland)
Practical Information
Literature
We will mostly be reading literature that is available online. Obligatory readings are either accessible through open access or online through SmartCat of the library.
Brightspace
We use the virtual learning environment “Brightspace” as the main platform for communication. If there is any necessary change on the syllabus, I will announce it in class and in Brightspace.
Assessment
| Assignment | % |
|---|---|
| Wiki page 1 | 20 |
| Wiki page 2 | 20 |
| Wiki page 3 | 20 |
| Talking clock | 10 |
| Talking clock presentation | 10 |
| Participation activities | 20 |
| TOTAL | 100 |
Assignments
Assignment 1: Wiki page on the history of speech recognition
Assignment 2: Wiki page on the history of speech synthesis
Assignment 3: Wiki page
Talking clock
Talking clock presentation
In class activities and participation
There are multiple ways to participate in class aside from talking. Therefore participation will be assessed in an inclusive way taking into account your engagement in group/individual activities, your connections with guest speakers, any additional peer review activities, and the way in which you support the class overall. To those ends, I’ll take into account your self-assessment which you will deliver to me via a form.