MATH · IN · MODELS

WavLM

Microsoft

Papers

[b]=[d]-[t]+[p]: Self-Supervised Speech Models Discover Phonological Vector Arithmetic (2026), Abstraction Induces the Brain Alignment of Language and Speech Models (2026), Dimensionality-Aware Anomaly Detection in Learned Representations of Self-Supervised Speech Models (2026), Eta-WavLM: Efficient Speaker Identity Removal in Self-Supervised Speech Representations Using a Simple Linear Equation (2025), InsideSSL: Understanding Self-Supervised Speech Representations using a Model-Centric Perspective (2026), Sparse Autoencoders Make Audio Foundation Models More Explainable (2025), Self-Supervised Speech Models Encode Phonetic Context via Position-dependent Orthogonal Subspaces (2026), Learning Arousal-Valence Representation from Categorical Emotion Labels of Speech (2023)