This document summarizes a university lecture on intelligent interfaces and automatic speech recognition. It discusses adaptive user interfaces and design guidelines, as well as trends, applications, and challenges of ASR systems. The lecture covers stimulus-response compatibility principles for interface design, applications of ASR in telecommunications, healthcare, and aviation, and challenges of ASR like varying accents and noise.

1. ICS3211 - Intelligent
Interfaces II
Combining design with technology for effective human-
computer interaction
Week 7 Department of AI,
University of Malta

2. Design & ASRs
Week 7 overview:
• Adaptive UIs and Design guidelines for UIs;
• Automatic Speech Recognition;

3. Learning Outcomes
At the end of this session you should be able to:
• Characterise ASR systems, with recent advancements
and identify challenges in their development

4. Lecture Outline
• ASR: trends, applications & challenges

5. Recap: VUIs
• Context awareness;
• Pervasive information visualisation;
• Ontologies in information visualisation;
• Information visualisation services;

7. Designing for Human
Information Processing
• Stimulus- Response compatibility: classes;
• S-S
• S-R
• S-C-R
• R-R
• R-E

8. • Stimulus- Response compatibility:
• S-S
• S-R
• S-C-R
• R-R
• R-E

9. • Compatibilities between alternate displays,
responses and consequences play important role
• Spatial compatibility for any task with spatial
properties
• Performance limitations from incompatibilities
cannot be easily overcome
• Use of Simon-type correspondence effects
• Compatibility issues arise for binary choices as well
as multiple task contexts

10. • More direct input manipulation requires taking into
consideration compatibility effects between
responses
• C:D relations can be optimised by adhering to
population stereotypes
• High compatibility essential for products intended
for use by older adults

11. Automatic Speech
Recognition
• Real life examples where such ASR have its
benefits include for accessibility for the visually
impaired
• A recent paper: "Intelligent Human-Robot
Interaction Using Voice Commands and Machine
Learning" Authors: Chen,L.,Wang,Y., Liu, J.
Published: 2020

12. Automatic Speech
Recognition
• ASR can be categorised depending on various
factors:

13. Speech Recognition
Techniques
• The SR system combines three stages:

14. Advancements in ASR
Systems
• ASR Using Deep Learning
• Speech Emotion Recognition Systems
• Development of Tools for High-Performance
Speech Recognition Systems

15. Applications of ASR
Systems
• Telecommunications Industry
• Emotion Recognition
• Healthcare Industry
• Aviation Industry

16. Challenges in ASR Systems
• Variation in Accents
• Children-centric Focus
• Model Training
• Noise

17. Class Task
Form groups and check the VLE Class discussion
area. Follow the guidelines to discuss the task in
terms of:
• Current State of the Art in Chatbot development
• User Experience and Engagement
• Challenges and Limitations
• Integration and Future Potential

18. –Rick Rashid
“These devices will eventually replace paper
print media. We are reaching a point in the
future where any surface can be an interactive
surface.”