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Conclusion We presented a factor-partitioned embedding framework for speech that supports similarity search across multiple attribute axes simultaneously

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eess.AS 1

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2026 1

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UNVERDICTED 1

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Multi-Axis Speech Similarity via Factor-Partitioned Embeddings

eess.AS · 2026-05-04 · unverdicted · novelty 6.0

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.

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  • Multi-Axis Speech Similarity via Factor-Partitioned Embeddings eess.AS · 2026-05-04 · unverdicted · none · ref 10

    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.