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20172026
most citedAdversarial Machine Learning And Speech Emotion Recognition: Utilizing Generative Adversarial Networks For Robustness

41 citations · 116 across the 18 of their papers we have counts for

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15 papers · 1 filter

cs.SD202311 cited

Sparks of Large Audio Models: A Survey and Outlook

Siddique Latif, Moazzam Shoukat, Fahad Shamshad +8

This survey paper provides a comprehensive overview of the recent advancements and challenges in applying large language models to the field of audio signal processing. Audio proce…

cs.SD20236 cited

Can Large Language Models Aid in Annotating Speech Emotional Data? Uncovering New Frontiers

Siddique Latif, Muhammad Usama, Mohammad Ibrahim Malik +1

Despite recent advancements in speech emotion recognition (SER) models, state-of-the-art deep learning (DL) approaches face the challenge of the limited availability of annotated d…

cs.SD2023

A Preliminary Study on Augmenting Speech Emotion Recognition using a Diffusion Model

Ibrahim Malik, Siddique Latif, Raja Jurdak +1

In this paper, we propose to utilise diffusion models for data augmentation in speech emotion recognition (SER). In particular, we present an effective approach to utilise improved…

cs.SD20236 cited

Emotions Beyond Words: Non-Speech Audio Emotion Recognition With Edge Computing

Ibrahim Malik, Siddique Latif, Sanaullah Manzoor +3

Non-speech emotion recognition has a wide range of applications including healthcare, crime control and rescue, and entertainment, to name a few. Providing these applications using…

cs.SD20231 cited

Lightweight Toxicity Detection in Spoken Language: A Transformer-based Approach for Edge Devices

Ahlam Husni Abu Nada, Siddique Latif, Junaid Qadir

Toxicity is a prevalent social behavior that involves the use of hate speech, offensive language, bullying, and abusive speech. While text-based approaches for toxicity detection a…

cs.SD20232 cited

Generative Emotional AI for Speech Emotion Recognition: The Case for Synthetic Emotional Speech Augmentation

Abdullah Shahid, Siddique Latif, Junaid Qadir

Despite advances in deep learning, current state-of-the-art speech emotion recognition (SER) systems still have poor performance due to a lack of speech emotion datasets. This pape…