Intro to Voice Technology syllabus

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:

1. explain the history of voice technology.
2. explain the basic elements of speech synthesis and recognition.
3. identify data resources for voice technology applications and know where to find them.
4. describe data management requirements for collecting and storing speech and speaker data.
5. elaborate on the value and relative importance of data management, licensing and privacy issues concerning speech and speaker data.
6. describe core aspects within speech production and feature extraction.
7. discuss with peers how human factors and relevant aspects of context affect the interaction between humans and voice technology systems.
8. 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

Wiki page 1: Make a Wiki page of a major event in the history of speech recognition. The page must link to 2 other pages and follow the template provided.[Assignment 1]

Wiki page 2: Make a Wiki page of a major event in the history of speech synthesis. The page must link to 2 other pages and follow the template provided. [Assignment 2]

Wiki page 3: Make a Wiki page in groups about different aspects of data management. The page must link to other pages by peers and adhere to the template [Assignment 3]

Talking clock: The talking clock assignment is performed partially in the Python course and partially in this course. While the Python course assesses the code, this course assesses the user interface, the functionality, and the creativity.

In class activities: Complete all pass/fail in-class activities and participate in discussions.

Participation: We believe that 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.