  Style transfer TTS has shown impressive performance in recent years. However,
style control is often restricted to systems built on expressive speech
recordings with discrete style categories. In practical situations, users may
be interested in transferring style by typing text descriptions of desired
styles, without the reference speech in the target style. The text-guided
content generation techniques have drawn wide attention recently. In this work,
we explore the possibility of controllable style transfer with natural language
descriptions. To this end, we propose PromptStyle, a text prompt-guided
cross-speaker style transfer system. Specifically, PromptStyle consists of an
improved VITS and a cross-modal style encoder. The cross-modal style encoder
constructs a shared space of stylistic and semantic representation through a
two-stage training process. Experiments show that PromptStyle can achieve
proper style transfer with text prompts while maintaining relatively high
stability and speaker similarity. Audio samples are available in our demo page.
