CSE 5525
Transcript Abbreviation:
Spch & Lang Proc
Course Description:
Fundamentals of natural language processing, automatic speech recognition and speech synthesis; lab projects concentrating on building systems to process written and/or spoken language.
Course Levels:
Undergraduate (1000-5000 level)
Graduate
Designation:
Elective
General Education Course
(N/A)
Cross-Listings
(N/A)
Credit Hours (Minimum if “Range”selected):
3.00
Max Credit Hours
(N/A)
Select if Repeatable:
Off
Maximum Repeatable Credits
(N/A)
Total Completions Allowed
(N/A)
Allow Multiple Enrollments in Term:
No
Course Length:
14 weeks (autumn or spring)
12 weeks (summer only)
Off Campus:
Never
Campus Location:
Columbus
Instruction Modes:
In Person (75-100% campus; 0-24% online)
Prerequisites and Co-requisites:
Prereq: 3521 or 5521, and 5522, Stat 3460, or 3470.
Electronically Enforced:
No
Exclusions:
Not open to students with credit for 733.
Course Goals / Objectives:
Master the fundamentals of symbolic methods in language processing tasks, such as natural language parsing
Be competent with fundamental concepts for natural language processing and automatic speech recognition, such as "hidden Markov models"
Be competent with fundamental concepts in text-to-speech synthesis, such as concatenative synthesis and text analysis
Be familiar with a finite state framework integrating all of speech processing
Be familiar with a toolkit for text classification, part-of-speech tagging and sentiment mining
Be familiar with methods of constructing speech recognition and synthesis systems.
Be exposed to current speech and language processing research
Be exposed to toolkits for speech recognition and speech synthesis
Check if concurrence sought:
No
Contact Hours:
| Topic | LEC | REC | LAB | LAB Inst |
|---|---|---|---|---|
| Course introduction, part-of-speech tagging | 3.0 | 0.0 | 0.0 | 0 |
| HMMs, expectation maximization and search | 3.0 | 0.0 | 0.0 | 0 |
| Parsing | 3.0 | 0.0 | 0.0 | 0 |
| Word senses | 3.0 | 0.0 | 0.0 | 0 |
| Language modeling | 3.0 | 0.0 | 0.0 | 0 |
| Text classification and opinion mining | 3.0 | 0.0 | 0.0 | 0 |
| Human hearing, acoustics, and phonetics | 3.0 | 0.0 | 0.0 | 0 |
| Finite state transducers and automatic speech recognition toolkits | 3.0 | 0.0 | 0.0 | 0 |
| Dynamic time warping and acoustic modeling | 3.0 | 0.0 | 0.0 | 0 |
| Text analysis and speech synthesis | 3.0 | 0.0 | 0.0 | 0 |
| Language processing in context (systems) | 3.0 | 0.0 | 0.0 | 0 |
| Quizzes and in-class assignments | 2.0 | 0.0 | 0.0 | 0 |
| Project presentations | 4.0 | 0.0 | 0.0 | 0 |
| Total | 39 | 0 | 0 | 0 |
Grading Plan:
Letter Grade
Course Components:
Lecture
Grade Roster Component:
Lecture
Credit by Exam (EM):
No
Grades Breakdown:
| Aspect | Percent |
|---|---|
| Labs and homeworks | 40% |
| Final project | 30% |
| Exams (2 x 10%) | 20% |
| Class Participation | 10% |
Representative Textbooks and Other Course Materials:
| Title | Author | Year |
|---|---|---|
| Speech and Language Processing, 2nd Edition | D. Jurafsky and J. Martin | |
| Speech Synthesis and Recognition, 2nd edition | J. Holmes and W. Holmes | |
| Spoken Language Processing: A guide to theory, algorithms, and system development | X. Huang, A. Acero, and H.-W. Hon |
ABET-CAC Criterion 3 Outcomes:
| Outcome | Contribution | Description |
|---|---|---|
| 1 | Substantial contribution (3-6 hours) | Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions. |
| 2 | Significant contribution (7+ hours) | Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline. |
| 3 | Some contribution (1-2 hours) | Communicate effectively in a variety of professional contexts. |
| 4 | Some contribution (1-2 hours) | Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles |
| 5 | Some contribution (1-2 hours) | Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline |
| 6 | Substantial contribution (3-6 hours) | Apply computer science theory and software development fundamentals to produce computing-based solutions. |
ABET-ETAC Criterion 3 Outcomes
(N/A)
ABET-EAC Criterion 3 Outcomes:
| Outcome | Contribution | Description |
|---|---|---|
| 1 | Substantial contribution (3-6 hours) | an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics |
| 2 | Significant contribution (7+ hours) | an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors |
| 3 | Some contribution (1-2 hours) | an ability to communicate effectively with a range of audiences - pre-2019 EAC SLO (g) |
| 4 | Some contribution (1-2 hours) | an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts |
| 5 | Some contribution (1-2 hours) | an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives |
| 6 | Substantial contribution (3-6 hours) | an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions |
| 7 | Some contribution (1-2 hours) | an ability to acquire and apply new knowledge as needed, using appropriate learning strategies |
Embedded Literacies Info
(N/A)
Attachments
(N/A)
Additional Notes or Comments
(N/A)