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Learning Outcomes:
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Cognitive (Knowledge, Understanding, Application, Analysis, Evaluation, Synthesis)
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On successful completion of this module, students will be able to:
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Identify the fundamental components of a Conversational AI (CAI) system
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Decode elementary speech patterns for use in CAI systems.
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Determine intent from uttered speech data in CAI systems.
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Explain how computer controlled responses are generated in modern CAI systems
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Affective (Attitudes and Values)
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On successful completion of this module, students will be able to:
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Explain the difference between a scripted Chatbot and a conversational artificial intelligence system.
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Characterise the performance of a CAI system.
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Demonstrate an understanding of how useful information is extracted from raw speech in CAI systems.
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Psychomotor (Physical Skills)
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N/A
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How the Module will be Taught and what will be the Learning Experiences of the Students:
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Materials will be delivered in a blended manner through weekly pre-recorded sessions and live class sessions. The course 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 participants' practical skills.
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Research Findings Incorporated in to the Syllabus (If Relevant):
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Prime Texts:
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Jurafsky, Daniel, & Martin, James H. (2008) Speech and Language Processing: International Version: an Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, Pearson
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Uday, K. and Liu, J. (2020) Deep Learning for NLP and Speech Recognition, Springer
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Other Texts:
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Wu Chou,& Biing-Hwang Juang (2005) Pattern Recognition in Speech and Language Processing (Electrical Engineering & Applied Signal Processing Series), CRC Press
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Rabiner, L. and Schafer, R. (2010) Theory and Applications of Digital Speech Processing, Pearson
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Programmes
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Semester(s) Module is Offered:
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Spring
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Module Leader:
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Generic PRS
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________________
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Module Code - Title:
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CE2012 - PROGRAMMING FOUNDATIONS FOR CONVERSATIONAL AI
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Year Last Offered:
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2020/1
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Hours Per Week
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Lecture
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Lab
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Tutorial
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Other
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Private
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Credits
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1
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0
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1
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0
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3
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3
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