Apple researchers develop theoretical framework to interpret acoustic embeddings using probabilistic distance measurements

Introduces probabilistic interpretation of distances between acoustic neighbor embeddings for understanding phonetic content

Proposes quantitative definition of phonetic similarity between words to enable principled application of embeddings

Demonstrates uniform cluster-wise isotropy approximation through theoretical and empirical evidence

Enables fixed-dimensional representation of variable-width audio or text in embedding space