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Research · Apple Machine Learning

A Theoretical Framework for Acoustic Neighbor Embeddings

This paper provides a theoretical framework for interpreting acoustic neighbor embeddings, which are representations of the phonetic content of variable-width audio or text in a fixed-dimensional embedding space.

Apr 09, 2026 00:00 UTC · ~4 min read · Primary Source
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Key Takeaways

  • A probabilistic interpretation of the distances between embeddings is proposed, based on a general quantitative definition of phonetic similarity between words.
  • This provides us a framework for understanding and applying the embeddings in a principled manner.
  • Theoretical and empirical evidence to support an approximation of uniform cluster-wise isotropy are shown, which allows us to…

Why It Matters

Context

A probabilistic interpretation of the distances between embeddings is proposed, based on a general quantitative definition of phonetic similarity between words. This provides us a framework for understanding and applying the embeddings in a principled manner. Theoretical and empirical evidence to support an approximation of uniform cluster-wise isotropy are shown, which allows us to…

For Builders

A probabilistic interpretation of the distances between embeddings is proposed, based on a general quantitative definition of phonetic similarity between words.