16 citations · 63 across the 8 of their papers we have counts for
8 papers
Representation Learning with Parameterised Quantum Circuits for Advancing Speech Emotion Recognition
Thejan Rajapakshe, Rajib Rana, Farina Riaz +2
Quantum machine learning (QML) offers a promising avenue for advancing representation learning in complex signal domains. In this study, we investigate the use of parameterised qua…
emoDARTS: Joint Optimisation of CNN & Sequential Neural Network Architectures for Superior Speech Emotion Recognition
Thejan Rajapakshe, Rajib Rana, Sara Khalifa +3
Speech Emotion Recognition (SER) is crucial for enabling computers to understand the emotions conveyed in human communication. With recent advancements in Deep Learning (DL), the p…
Enhancing Speech Emotion Recognition Through Differentiable Architecture Search
Thejan Rajapakshe, Rajib Rana, Sara Khalifa +2
Speech Emotion Recognition (SER) is a critical enabler of emotion-aware communication in human-computer interactions. Recent advancements in Deep Learning (DL) have substantially e…
Domain Adapting Deep Reinforcement Learning for Real-world Speech Emotion Recognition
Thejan Rajapakshe, Rajib Rana, Sara Khalifa +1
Computers can understand and then engage with people in an emotionally intelligent way thanks to speech-emotion recognition (SER). However, the performance of SER in cross-corpus a…
A novel policy for pre-trained Deep Reinforcement Learning for Speech Emotion Recognition
Thejan Rajapakshe, Rajib Rana, Sara Khalifa +2
Reinforcement Learning (RL) is a semi-supervised learning paradigm which an agent learns by interacting with an environment. Deep learning in combination with RL provides an effici…
Deep Reinforcement Learning with Pre-training for Time-efficient Training of Automatic Speech Recognition
Thejan Rajapakshe, Siddique Latif, Rajib Rana +2
Deep reinforcement learning (deep RL) is a combination of deep learning with reinforcement learning principles to create efficient methods that can learn by interacting with its en…
Pre-training in Deep Reinforcement Learning for Automatic Speech Recognition
Thejan Rajapakshe, Rajib Rana, Siddique Latif +2
Deep reinforcement learning (deep RL) is a combination of deep learning with reinforcement learning principles to create efficient methods that can learn by interacting with its en…
Improving Assessment on MOOCs Through Peer Identification and Aligned Incentives
Dilrukshi Gamage, Mark Whiting, Thejan Rajapakshe +3
Massive Open Online Courses (MOOCs) use peer assessment to grade open ended questions at scale, allowing students to provide feedback. Relative to teacher based grading, peer asses…