  As an indispensable part of modern human-computer interaction system, speech
synthesis technology helps users get the output of intelligent machine more
easily and intuitively, thus has attracted more and more attention. Due to the
limitations of high complexity and low efficiency of traditional speech
synthesis technology, the current research focus is the deep learning-based
end-to-end speech synthesis technology, which has more powerful modeling
ability and a simpler pipeline. It mainly consists of three modules: text
front-end, acoustic model, and vocoder. This paper reviews the research status
of these three parts, and classifies and compares various methods according to
their emphasis. Moreover, this paper also summarizes the open-source speech
corpus of English, Chinese and other languages that can be used for speech
synthesis tasks, and introduces some commonly used subjective and objective
speech quality evaluation method. Finally, some attractive future research
directions are pointed out.
