A factor-partitioned embedding framework maps speech utterances to vectors with subspaces for distinct attributes, supporting signed weighted similarity retrieval that can suppress or emphasize specific factors like speaker identity.
Measuring the perceptual effects of modelling assumptions in speech synthesis using stimuli constructed from repeated natural speech,
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Multi-Axis Speech Similarity via Factor-Partitioned Embeddings
A factor-partitioned embedding framework maps speech utterances to vectors with subspaces for distinct attributes, supporting signed weighted similarity retrieval that can suppress or emphasize specific factors like speaker identity.