MA-INF 4238: DIALOGUE SYSTEMS
Summer Semester 2024
Content:
What is the Dialogue Systems course about?
This course is a detailed introduction to the architecture of conversational systems (chatbots). We will introduce the main components of dialog systems and show approaches to their implementation, including natural language understanding, natural language generation, and dialog sequence management. This course will briefly discuss speech-related components and multi-modal systems, but will primarily focus on text processing and language understanding. The lab sessions will be dedicated to implementing a simple dialog system and selected components (via weekly homework assignments).
Recommended participation requirements:
There are no mandatory prerequisites but the following will help you understand the material:
- Introduction to Natural Language Processing
- Introduction to Machine Learning
- Basics of statistics
- Basics of programming (Python)
Logistics:
- Lectures: are on Thursday 12:15 PM - 01:45 PM in Room 0.109 (B-IT-Max) (Friedrich-Hirzebruch-Allee 6). ZOOM LINK
- Exercises: are on Thursday 02:15 PM - 03:45 AM in Room 0.109 (B-IT-Max) (Friedrich-Hirzebruch-Allee 6). ZOOM LINK
- Course Materials: will be uploaded every week on eCampus.
- Contact: Students should ask all course-related questions in our forum discussion on eCampus. For external inquiries, emergencies, or personal matters, you can contact Prof. Flek, AK, or Mounika.
- Office Hours: Please reach out to us first via mail to arrange any in-person meeting.
- Prof. Dr. Lucie Flek: Friedrich-Hirzebruch-Allee 6 (B-IT) – Room: 2.123
- Dr. Akbar Karimi (AK): Friedrich-Hirzebruch-Allee 6 (B-IT) – Room: 2.118
- Dr. Mounika Marreddy: Friedrich-Hirzebruch-Allee 6 (B-IT) – Room: 2.119
NEWS / UPDATES:
- 01.04.2024: The first class will take place on Thursday, 18.04.2024 at 12:15 in Room 0.109 (B-IT-Max).
Instructors:
Coursework:
Assignments (10%):
Will be uploaded on eCampus.
- Credits:
- Assignment 1 (5%):
- Assignment 2 (5%):
- Deadlines: All assignments are due on Wednesdays before the exercise class at 11:59 PM. All deadlines are listed in the schedule.
- Submission: Assignments should be submitted via eCampus. Please do not email us your assignments.
- Collaboration: Each student should work on the assignment individually. Please name your file properly. File name: <FirstName_LastName>.
- Grade/ Feedback: You will receive your graded assignment on eCampus.
**NOTE**: The assignments are not prerequisite for the exam.
Final Project (30%):
- Project Types:
- Checkpoint 1 (2%)
- Checkpoint 1 (3%)
- Oral presentation (5%)
- Final report (10%)
- (Code and) Dataset (10%)
- Deadline: July 10, 2024 (tentative)
- Contribution: Students will be encouraged to form groups of 3-4 people for the project.
- Grade/ Feedback: You will receive your graded assignment on eCampus.
Exam (60%):
- Exam dates: will be announced as soon as we receive the rooms and dates from the examination office.
- Allowed material: Calculators are permitted.
Allocation:
- 3 + 1 SWS
- Master in Media Informatics: 4 ECTS credits
- Master in computer science at University of Bonn: MA-INF 4238 6 CP
- Students must register for the exam on POS/BASIS.
Literature:
- Jurafsky, D., & Martin, J. E. Speech & Language Processing, An Introduction to Natural Language Processing, Computational Linguistics & Speech Recognition
- Goodfellow, I., Bengio, Y., & Courville, A. Deep Learning. MIT Press.
- McTear, M. Spoken Dialogue Technology: Enabling the Conversational User Interface. ACM.
Schedule:
| Week | Date | Description | Events | Deadlines |
|---|---|---|---|---|
| Week 1 | Lecture (Thursday Apr 18) | |||
| Exercise (Thursday Apr 18) | ||||
| Week 2 | Lecture (Thursday) | |||
| Exercise (Thursday) | Assignment 1 OUT | |||
| Week 3 | Lecture (Thursday) | |||
| Exercise (Thursday) | Project OUT | Assignment 1 DUE | ||
| Week 4 | Lecture (Thursday) | |||
| Exercise (Thursday) | Assignment 2 OUT | |||
| Week 5 | Lecture (Thursday) | |||
| Exercise (Thursday) | ||||
| Week 6 | Lecture (Thursday) | |||
| Exercise (Thursday) | Assignment 2 DUE | |||
| Week 7 | Lecture (Thursday) | |||
| Exercise (Thursday) | ||||
| Week 8 | Lecture (Thursday) | |||
| Exercise (Thursday) | ||||
| Week 9 | Lecture (Thursday) | |||
| Exercise (Thursday) | ||||
| Week 10 | Lecture (Thursday) | |||
| Exercise (Thursday) | ||||
| Week 11 | Lecture (Thursday) | |||
| Exercise (Thursday) | ||||
| Week 12 | Lecture (Thursday) | |||
| Exercise (Thursday) |