Papers by Tyler Miller

1 papers
Text-Free Image-to-Speech Synthesis Using Learned Segmental Units (2021.acl-long)

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Challenge: Existing models for synthesising fluent, natural-sounding spoken audio captions do not require natural language text as an intermediate representation or source of supervision.
Approach: They propose a model for directly synthesizing fluent, natural-sounding spoken audio captions for images that does not require natural language text as an intermediate representation or source of supervision.
Outcome: The proposed model captures diverse visual semantics of images and can replace text with a set of discrete, sub-word speech units.

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