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20182025
most citedDeep Representation Learning in Speech Processing: Challenges, Recent Advances, and Future Trends

68 citations · 134 across the 15 of their papers we have counts for

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Showing 2020Show all

7 papers · 1 filter

eess.AS2020★ 11 cited

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…

cs.SD2020

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…

cs.SD2020

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…

eess.SP2020★ 6 cited

Task Scheduling for Simultaneous IoT Sensing and Energy Harvesting: A Survey and Critical Analysis

Muhammad Moid Sandhu, Sara Khalifa, Raja Jurdak +1

The Internet of Things (IoT) has important applications in our daily lives including health and fitness tracking, environmental monitoring and transportation. However, sensor nodes…

eess.SP2020

Towards Optimal Kinetic Energy Harvesting for the Batteryless IoT

Muhammad Moid Sandhu, Kai Geissdoerfer, Sara Khalifa +3

Traditional Internet of Things (IoT) sensors rely on batteries that need to be replaced or recharged frequently which impedes their pervasive deployment. A promising alternative is…

eess.SP2020

Towards Energy Positive Sensing using Kinetic Energy Harvesters

Muhammad Moid Sandhu, Kai Geissdoerfer, Sara Khalifa +3

Conventional systems for motion context detection rely on batteries to provide the energy required for sampling a motion sensor. Batteries, however, have limited capacity and, once…

cs.SD2020★ 68 cited

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…