Jumon Nozaki


2022

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Addressing Segmentation Ambiguity in Neural Linguistic Steganography
Jumon Nozaki | Yugo Murawaki
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)

Previous studies on neural linguistic steganography, except Ueoka et al. (2021), overlook the fact that the sender must detokenize cover texts to avoid arousing the eavesdropper’s suspicion. In this paper, we demonstrate that segmentation ambiguity indeed causes occasional decoding failures at the receiver’s side. With the near-ubiquity of subwords, this problem now affects any language. We propose simple tricks to overcome this problem, which are even applicable to languages without explicit word boundaries.
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