  Generative AI has demonstrated impressive performance in various fields,
among which speech synthesis is an interesting direction. With the diffusion
model as the most popular generative model, numerous works have attempted two
active tasks: text to speech and speech enhancement. This work conducts a
survey on audio diffusion model, which is complementary to existing surveys
that either lack the recent progress of diffusion-based speech synthesis or
highlight an overall picture of applying diffusion model in multiple fields.
Specifically, this work first briefly introduces the background of audio and
diffusion model. As for the text-to-speech task, we divide the methods into
three categories based on the stage where diffusion model is adopted: acoustic
model, vocoder and end-to-end framework. Moreover, we categorize various speech
enhancement tasks by either certain signals are removed or added into the input
speech. Comparisons of experimental results and discussions are also covered in
this survey.
