128 citations · 341 across the 20 of their papers we have counts for
6 papers · 1 filter
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…
Guided Generative Adversarial Neural Network for Representation Learning and High Fidelity Audio Generation using Fewer Labelled Audio Data
Kazi Nazmul Haque, Rajib Rana, John H. L. Hansen +1
Recent improvements in Generative Adversarial Neural Networks (GANs) have shown their ability to generate higher quality samples as well as to learn good representations for transf…
Deep Representation Learning in Speech Processing: Challenges, Recent Advances, and Future Trends
Siddique Latif, Rajib Rana, Sara Khalifa +3
Research on speech processing has traditionally considered the task of designing hand-engineered acoustic features (feature engineering) as a separate distinct problem from the tas…