（注：本文内容改编自LetPub）

29. 撰写摘要。摘要部分不该留有任何多余的空间。每一个字的存在都要是有目的的。摘要中的结论不应该重申结果。最重要和有效的数据应该结合数字来表达。大多数读者可能只会阅读摘要，因此要确保你在摘要中明确表述出你的最重要的信息。

附个例子吧（并不是所有的摘要都必须以这样的结构和顺序写，但以下写法比较保险）

Abstract (of "SEGAN: Speech Enhancement Generative Adversarial Network")

(Background/Rationale:) Current speech enhancement techniques operate on the spectral domain and/or exploit some higher-level feature. The majority of them tackle a limited number of noise conditions and rely on first-order statistics. To circumvent these issues, deep networks are being increasingly used, thanks to their ability to learn complex functions from large example sets.

(Objective/Methods:) In this work, we propose the use of generative adversarial networks for speech enhancement. In contrast to current techniques, we operate at the waveform level, training the model end-to-end, and incorporate 28 speakers and 40 different noise conditions into the same model, such that model parameters are shared across them. 

(Results:) We evaluate the proposed model using an independent, unseen test set with two speakers and 20 alternative noise conditions. The enhanced samples confirm the viability of the proposed model, and both objective and subjective evaluations confirm the effectiveness of it. 

(Conclusions:) With that, we open the exploration of generative architectures for speech enhancement, which may progressively incorporate further speech-centric design choices to improve their performance.