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Interpreting Content and Speaker Characteristics in Factorised Self-Supervised Subspaces
Self-supervised speech features encode both content and speaker information. Recent work introduced an SVD-based factorisation method that decomposes these features into a shared content matrix capturing temporal variation and speaker-specific transformations capturing static speaker characteristics
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