87 citations · 387 across the 34 of their papers we have counts for
9 papers · 1 filter
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…
Cross-Language Speech Emotion Recognition Using Multimodal Dual Attention Transformers
Syed Aun Muhammad Zaidi, Siddique Latif, Junaid Qadir
Despite the recent progress in speech emotion recognition (SER), state-of-the-art systems are unable to achieve improved performance in cross-language settings. In this paper, we p…
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…
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…
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…
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…
MESAHA-Net: Multi-Encoders based Self-Adaptive Hard Attention Network with Maximum Intensity Projections for Lung Nodule Segmentation in CT Scan
Muhammad Usman, Azka Rehman, Abd Ur Rehman +5
Accurate lung nodule segmentation is crucial for early-stage lung cancer diagnosis, as it can substantially enhance patient survival rates. Computed tomography (CT) images are wide…
Transformers in Speech Processing: A Survey
Siddique Latif, Aun Zaidi, Heriberto Cuayahuitl +4
The remarkable success of transformers in the field of natural language processing has sparked the interest of the speech-processing community, leading to an exploration of their p…
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…