Steganography is the art of hiding a secret message inside a publicly visible carrier message. Ideally, it is done without modifying the carrier, and with minimal loss of information in the secret message. Recently, various deep learning based approaches to steganography have been applied to different message types. We propose a deep learning based technique to hide a source RGB image message inside finite length speech segments without perceptual loss. To achieve this, we train three neural networks; an encoding network to hide the message in the carrier, a decoding network to reconstruct the message from the carrier and an additional image enhancer network to further improve the reconstructed message. We also discuss future improvements to the algorithm proposed.

中文翻译：

---

语音隐写术中图像的深度残差神经网络

隐写术是将秘密信息隐藏在公开可见的载体信息中的艺术。理想情况下，无需修改载体即可完成，并且秘密消息中的信息丢失最少。最近，各种基于深度学习的隐写术方法已应用于不同的消息类型。我们提出了一种基于深度学习的技术，将源 RGB 图像消息隐藏在有限长度的语音段内，而不会造成感知损失。为此，我们训练了三个神经网络；一个编码网络将消息隐藏在载体中，一个解码网络从载体中重建消息，以及一个附加的图像增强器网络，以进一步改进重建的消息。我们还讨论了对所提出算法的未来改进。