Lecture 02-Jan 15_Relevant concepts I

Course Overview

• Course Title: UGS 303 Communication and AI

• Instructor: Jun Wang, Ph.D.

  • Affiliations:

    • Department of Speech, Language, and Hearing Sciences, Moody College of Communication

    • Department of Neurology, Dell Medical School

Learning Objectives

• CLO1: Understand the basic mechanisms through which humans produce, hear, perceive speech, and understand language.

• CLO2: Comprehend the nature of AI, including algorithms and programs.

• CLO3: Explore how AI performs tasks related to communication.

Syllabus Details

• Prerequisites: None

• Textbook: Not required

Academic Calendar

Week 1

• Jan 13: Course introduction; Introduction to relevant concepts: AI, machine learning, communication.

• Jan 15: Lecture on speech and language, the brain, assistive technologies.

• Jan 17: Practical class to install Matlab.

• Jan 20: No class (Martin Luther King Jr. Day).

Week 2

• Jan 22: Overview of common AI tools related to communication; Overview of basic programming.

• Jan 24: Get familiar with Matlab.

• Jan 27: Data structures topics.

Week 3

• Jan 29: Programming: Data structures, loops, control statements.

• Jan 31: Practice related to data structures.

Week 4

• Feb 05: File/Data Input/Output, algorithm debugging.

Week 5

• Feb 10: Graphical User Interface (GUI), data processing in GUI; Writing assignments distributed.

Week 6-10

• Feb 17: Signal processing lectures (analog vs digital, Fourier transform).

• Mar 12: Exam 1 covering Matlab programming and AI topics.

• Mar 26: Human voice and articulation systems discussion.

• Mar 28: Exam 2 on Human Communication Mechanisms.

Week 11-16

• Apr 18: Presentation of Projects I & II due.

• Apr 28: Last day of classes.

Assessment Overview

• Exam Types: Online and in-class, with special accommodations allowed.

• Grading Breakdown:

  • Survey: 3%

  • Exams: 30%

  • Projects: 30%

  • Read-and-rewrite assignment: 15%

  • Writing assignment: 15%

  • Attendance & Participation: 7%

  • Bonus quizzes: 3+ (extra)

Grading Scale

• A: 94 - 100

• A-: 90 - 93.9

• B+: 87 - 89.9

• B: 84 - 86.9

• B-: 80 - 83.9

• C+: 77 - 79.9

• C: 74 - 76.9

• C-: 70 - 73.9

• D+: 67 - 69.9

• D: 64 - 66.9

• D-: 60 - 63.9

• F: < 60

Exam Policies

• Exams must be completed within the specified time.

• Rescheduling only accepted with excused absences.

• Late assignments incurred 10% penalty per day.

Classroom Citizenship

• Expected behavior: Focus during class, no distractions (talking, texting, etc.).

Academic Integrity

• Essential for success; students must follow the university's Honor Code regarding originality and plagiarism.

Communication Tips for Students

• Use UT email for communication.

• Regularly check email for announcements and class updates.

• A profile picture on Canvas can boost participation scores.

Relevant Concepts in Course

• Computers & Computing

• Computer programming

• AI and Machine learning

• Speech and Language processes

• Neuroscience and Brain function

• Assistive Technologies related to communication.

Understanding Computers

Definitions

• Computer: Device executing sequences of instructions.

• Pre-AI Capabilities: What pre-AI computers can and cannot do.

Hardware Components

• Internal Hardware:

  • Motherboard, RAM, hard disk, CPU.

• External Hardware: Monitor, mouse, keyboard, printer.

Central Processing Unit (CPU)

• The "heart" or "power" of the computer, executing calculations and managing tasks.

Graphic Processing Unit (GPU)

• Specialized for digital imaging processing; excels in parallel processing used for AI Model training.

Binary Number System

• Bases on binary (0s and 1s) for circuit simplicity; low complexity in digital circuits.