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eess.AS2026

Exploring Second-Order Pattern Recognition in Speaker Recognition

Yanze Xu, Wenwu Wang, Mark D. Plumbley

In classical pattern recognition tasks, neural networks are trained to recognise human-defined patterns for model inputs. Some Explainable AI (XAI) methods can explain other latent…

eess.AS2026

Summary of DCASE 2026 Task 5: Audio-Dependent Question Answering

Haolin He, Renhe Sun, Zheqi Dai +16

DCASE~2026 Task~5 introduces Audio-Dependent Question Answering (ADQA), which tests whether large audio-language models answer from the audio rather than from textual priors. An Au…

eess.AS2026

Efficient Text-to-Audio Generation via Pruning

Arshdeep Singh, Yi Yuan, Yun Chen +2

Diffusion-based text-to-audio generative models such as AudioLDM achieve high perceptual quality and strong semantic consistency; however, their practical deployment is hindered by…

eess.AS2026

Explainable AI in Speaker Recognition -- Attention Map Visualisation and Evaluation

Yanze Xu, Mark D. Plumbley, Wenwu Wang

Explaining and understanding the decision-making process of artificial intelligence (AI) systems, particularly those implemented by neural networks, falls within the field of expla…

eess.AS2026

Explainable AI in Speaker Recognition -- Making Latent Representations Understandable

Yanze Xu, Wenwu Wang, Mark D. Plumbley

Neural networks can be trained to learn task-relevant representations from data. Understanding how these networks make decisions falls within the Explainable AI (XAI) domain. This…

eess.AS2026

BioDCASE 2026 Challenge Baseline for Cross-Domain Mosquito Species Classification

Yuanbo Hou, Vanja Zdravkovic, Marianne Sinka +5

Mosquito-borne diseases affect more than one billion people each year and cause close to one million deaths. Traditional surveillance methods rely on traps and manual identificatio…