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Recently, text-guided content generation has received extensive attention. Inthis work, we explore the possibility of text description-based speakergeneration, i.e., using text prompts to control the speaker generation process.Specifically, we propose PromptSpeaker, a text-guided speaker generationsystem. PromptSpeaker consists of a prompt encoder, a zero-shot VITS, and aGlow model, where the prompt encoder predicts a prior distribution based on thetext description and samples from this distribution to obtain a semanticrepresentation. The Glow model subsequently converts the semanticrepresentation into a speaker representation, and the zero-shot VITS finallysynthesizes the speaker's voice based on the speaker representation. We verifythat PromptSpeaker can generate speakers new from the training set by objectivemetrics, and the synthetic speaker voice has reasonable subjective matchingquality with the speaker prompt.

PromptSpeaker: Speaker Generation Based on Text Descriptions