Self-supervised speech encoders contain linguistic and paralinguistic information in a shared, entangled representation space. We combine a TopK sparse autoencoder with route-specific supervision and cross-factor adversaries. Across frozen SPEAR and WavLM encoders, independent probes show factor-specific retention and...
Beimnet Bekele Guta, Xiao-Yu Yang, Guang-Zhi Sun et al.· 0 citations
Speech understanding and generation place different demands on speech representations, and existing models are typically optimised towards one capability or the other. To reduce this gap, we introduce SPEAR-Gen, a speech representation model that learns a single representation for both capabilities. Task-aligned featur...
Xiao-Yu Yang, Arthur Hinsvark, Antonios Alexos et al.· 0 citations
Spectral-Aware Muon is introduced, which holds the head at the Muon scale and amplifies the bulk using a static spectral prior, and both variants outperform tuned AdamW and Muon (Scion implementation) baselines in all evaluated model-scale and batch-size configurations.
Xiaodong Wu, Wen-Yi Yu, Chao Zhang et al.· 1 citation
A multi-layer feature fusion (MLF) adapter that aggregates information from all encoder layers before projecting them into the language model is proposed and shows that MICL does not emerge naturally in ALLMs, but can be effectively acquired through targeted contextual biasing training.
Xiaoyu Yang, Xuenan Xu, Wenyi Yu et al.· 0 citations
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