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Explain the difference between a scripted Chatbot and a conversational artificial intelligence system. |
Critically assess the performance of a functioning CAI system. |
Psychomotor (Physical Skills) |
N/A |
How the Module will be Taught and what will be the Learning Experiences of the Students: |
Materials will be delivered in a blended manner through weekly pre-recorded sessions and live class sessions. The module material will include video recordings as well as readings, exercises, and assignments. The focus is on the reduction of theory to practice so there will be a strong emphasis on developing participan... |
Research Findings Incorporated in to the Syllabus (If Relevant): |
Prime Texts: |
Jurafsky, Daniel. |
and Martin, James H. (2008) Speech and Language Processing: International Edition, Pearson |
Other Texts: |
Kamath, Uday. and Liu, John. (2020) Deep Learning for NLP and Speech Recognition, Springer |
Programmes |
Semester(s) Module is Offered: |
Spring |
Module Leader: |
Generic PRS |
________________ |
Module Code - Title: |
CE2003 - THEORY AND PRACTICE FOR CONVERSATIONAL AI |
Year Last Offered: |
2020/1 |
Hours Per Week |
Lecture |
Lab |
Tutorial |
Other |
Private |
Credits |
2 |
0 |
2 |
0 |
6 |
6 |
Grading Type: |
N |
Prerequisite Modules: |
Rationale and Purpose of the Module: |
Conversational Artificial Intelligence (CAI) is the software and processes by which speech is transformed into input for computers and smart devices. |
This module will provide students with practical insights regarding the theoretical concepts that underpin modern Conversational AI systems. |
Syllabus: |
Introduction to machine learning for Conversational AI, (CAI). Scripted versus CAI systems for Human Computer spoken word interaction. |
Neural Networks for CAI. The definition and application of RNN, CNN, DNN, xNN subsystems to CAI. |
Speech recognition, language modeling and language decoding for CAI. Evaluation of Speech recognition tools. Data collection and labelling for training in CAI. Bag of words testing. An introduction to N-gram based modelling of speech. |
Evaluation of intent in CAI. Development of training sentences. Evaluation of Semantics, context and embedding in CAI systems. |
Dialog management: Introduction to Reasoning and Response generation in computer-based CAI systems. |
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