41 citations · 89 across the 10 of their papers we have counts for
18 papers
AI-Based Emotion Recognition: Promise, Peril, and Prescriptions for Prosocial Path
Siddique Latif, Hafiz Shehbaz Ali, Muhammad Usama +3
Automated emotion recognition (AER) technology can detect humans' emotional states in real-time using facial expressions, voice attributes, text, body movements, and neurological s…
Self Supervised Adversarial Domain Adaptation for Cross-Corpus and Cross-Language Speech Emotion Recognition
Siddique Latif, Rajib Rana, Sara Khalifa +2
Despite the recent advancement in speech emotion recognition (SER) within a single corpus setting, the performance of these SER systems degrades significantly for cross-corpus and…
High-Fidelity Audio Generation and Representation Learning with Guided Adversarial Autoencoder
Kazi Nazmul Haque, Rajib Rana, Björn W Schuller
Unsupervised disentangled representation learning from the unlabelled audio data, and high fidelity audio generation have become two linchpins in the machine learning research fiel…
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…
Deep Architecture Enhancing Robustness to Noise, Adversarial Attacks, and Cross-corpus Setting for Speech Emotion Recognition
Siddique Latif, Rajib Rana, Sara Khalifa +2
Speech emotion recognition systems (SER) can achieve high accuracy when the training and test data are identically distributed, but this assumption is frequently violated in practi…
Augmenting Generative Adversarial Networks for Speech Emotion Recognition
Siddique Latif, Muhammad Asim, Rajib Rana +3
Generative adversarial networks (GANs) have shown potential in learning emotional attributes and generating new data samples. However, their performance is usually hindered by the…