  Using a text description as prompt to guide the generation of text or images
(e.g., GPT-3 or DALLE-2) has drawn wide attention recently. Beyond text and
image generation, in this work, we explore the possibility of utilizing text
descriptions to guide speech synthesis. Thus, we develop a text-to-speech (TTS)
system (dubbed as PromptTTS) that takes a prompt with both style and content
descriptions as input to synthesize the corresponding speech. Specifically,
PromptTTS consists of a style encoder and a content encoder to extract the
corresponding representations from the prompt, and a speech decoder to
synthesize speech according to the extracted style and content representations.
Compared with previous works in controllable TTS that require users to have
acoustic knowledge to understand style factors such as prosody and pitch,
PromptTTS is more user-friendly since text descriptions are a more natural way
to express speech style (e.g., ''A lady whispers to her friend slowly''). Given
that there is no TTS dataset with prompts, to benchmark the task of PromptTTS,
we construct and release a dataset containing prompts with style and content
information and the corresponding speech. Experiments show that PromptTTS can
generate speech with precise style control and high speech quality. Audio
samples and our dataset are publicly available.
