From the 2 of 21 linked papers with an AI index.
21 papers
FlowSep 2: Self-Supervised Flow Matching for Language-Queried Audio Source Separation
Yi Yuan, Xubo Liu, Haohe Liu +3
Language-queried audio source separation (LASS) aims to extract target sources from audio mixtures according to natural language descriptions, offering a flexible and scalable inte…
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…
Efficient Text-to-Audio Generation via Pruning
Arshdeep Singh, Yi Yuan, Yun Chen +2
The paper applies filter‑based pruning to the U‑Net backbone of the AudioLDM text‑to‑audio diffusion model, reducing most of its parameters and compute while preserving generation…
Teaching Speech Enhancement Models to Sing: Domain Adaptation from Speech Enhancement to Singing Voice Separation
Paul A. Bereuter, Mark D. Plumbley, Alois Sontacchi
The paper adapts pretrained speech enhancement models to perform singing voice separation using fine‑tuning and low‑rank adaptation, achieving better separation with limited singin…
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…
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…