ORCID Profile
0000-0002-3030-1280
Current Organisation
Nanyang Technological University
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Publisher: IEEE
Date: 07-2020
Publisher: Elsevier BV
Date: 09-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Elsevier BV
Date: 08-2016
Publisher: Springer Science and Business Media LLC
Date: 24-06-2021
Publisher: Elsevier BV
Date: 03-2018
Publisher: Springer Science and Business Media LLC
Date: 04-12-2018
Publisher: Elsevier BV
Date: 07-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2021
Publisher: MDPI AG
Date: 10-02-2023
Abstract: Video conferencing has enabled synchronous communication in a classroom and created multi-sensory content to stimulate learners. Artificial intelligence involves complex equations that are better taught using a constructive pedagogy where students experiment with alternative ways of solving the same problem. Multiple-choice questions have high reliability and can easily reveal student skill levels in a quick way. The Australian Computer Society accreditation exercise ensures that the content for each subject serves as a flexible template for teaching. The geographical extent of the country requires the presence of multiple subordinate c uses affiliated to a main c us. Following the concept of strands, it was also necessary to show continuity in learning and assessments between the first- and second-year subjects. Student feedback for subjects with artificial intelligence-based simulations showed that several students found it difficult to understand lectures and assignments. Hence, to measure student learning, we introduced a Kahoot quiz during the recess of each lecture that students could join through their mobile phones from different c uses. Software project management is challenging for students with vision or attention-related disorders. We taught them how to use charts to visually observe variables and narrow down possible relationships before performing in-depth analysis. One of the main purposes of education is employability. Hence, greater context to real world industry ex les was introduced into lectures.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2020
Publisher: Springer International Publishing
Date: 2015
Publisher: Elsevier BV
Date: 08-2019
Publisher: Springer Science and Business Media LLC
Date: 02-07-2022
DOI: 10.1007/S10462-022-10224-2
Abstract: Deep reinforcement learning (DRL) is poised to revolutionise the field of artificial intelligence (AI) by endowing autonomous systems with high levels of understanding of the real world. Currently, deep learning (DL) is enabling DRL to effectively solve various intractable problems in various fields including computer vision, natural language processing, healthcare, robotics, to name a few. Most importantly, DRL algorithms are also being employed in audio signal processing to learn directly from speech, music and other sound signals in order to create audio-based autonomous systems that have many promising applications in the real world. In this article, we conduct a comprehensive survey on the progress of DRL in the audio domain by bringing together research studies across different but related areas in speech and music. We begin with an introduction to the general field of DL and reinforcement learning (RL), then progress to the main DRL methods and their applications in the audio domain. We conclude by presenting important challenges faced by audio-based DRL agents and by highlighting open areas for future research and investigation. The findings of this paper will guide researchers interested in DRL for the audio domain.
Publisher: Elsevier BV
Date: 02-2021
Publisher: IEEE
Date: 05-2017
Publisher: Springer Science and Business Media LLC
Date: 20-08-2016
Publisher: IEEE
Date: 11-2017
Publisher: IEEE
Date: 07-2016
Publisher: Elsevier BV
Date: 03-2023
Publisher: IEEE
Date: 11-2017
Publisher: IEEE
Date: 12-2016
Publisher: IEEE
Date: 07-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2023
Publisher: Elsevier BV
Date: 11-2018
Publisher: Elsevier BV
Date: 11-2022
Publisher: Instituto Politecnico Nacional/Centro de Investigacion en Computacion
Date: 15-07-1970
Publisher: IEEE
Date: 11-2018
Publisher: Springer Science and Business Media LLC
Date: 16-06-2021
No related grants have been discovered for Erik Cambria.