41 citations · 145 across the 24 of their papers we have counts for
9 papers · 1 filter
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…
Unsupervised Adversarial Domain Adaptation for Cross-Lingual Speech Emotion Recognition
Siddique Latif, Junaid Qadir, Muhammad Bilal
Cross-lingual speech emotion recognition (SER) is a crucial task for many real-world applications. The performance of SER systems is often degraded by the differences in the distri…
Multi-Task Semi-Supervised Adversarial Autoencoding for Speech Emotion Recognition
Siddique Latif, Rajib Rana, Sara Khalifa +3
Inspite the emerging importance of Speech Emotion Recognition (SER), the state-of-the-art accuracy is quite low and needs improvement to make commercial applications of SER viable.…
Caveat emptor: the risks of using big data for human development
Siddique Latif, Adnan Qayyum, Muhammad Usama +3
Big data revolution promises to be instrumental in facilitating sustainable development in many sectors of life such as education, health, agriculture, and in combating humanitaria…
Disentangled Representation Learning with Information Maximizing Autoencoder
Kazi Nazmul Haque, Siddique Latif, Rajib Rana
Learning disentangled representation from any unlabelled data is a non-trivial problem. In this paper we propose Information Maximising Autoencoder (InfoAE) where the encoder learn…
Direct Modelling of Speech Emotion from Raw Speech
Siddique Latif, Rajib Rana, Sara Khalifa +2
Speech emotion recognition is a challenging task and heavily depends on hand-engineered acoustic features, which are typically crafted to echo human perception of speech signals. H…