Introduces truncation and Jacobian-based measures of effective context showing that self-supervised speech Transformers use a short, mostly local context and can be streamed with minor probing degradation.
Various speech tasks benefit from contextualized speech embeddings learned with self-supervision [1–5]
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Effective Context in Neural Speech Models
Introduces truncation and Jacobian-based measures of effective context showing that self-supervised speech Transformers use a short, mostly local context and can be streamed with minor probing degradation.