Rephrasing Profanity in Chinese Text
This paper proposes a system that can detect and rephrase profanity in Chinese text. Rather than just masking detected profanity, we want to revise the input sentence by using inoffensive words while keeping their original meanings. 29 of such rephrasing rules were invented after observing sentences on real-word social websites. The overall accuracy of the proposed system is 85.56{\%}
Code (0)
등록된 구현이 없습니다.
Tasks
SentenceSimilar Papers 제목 키워드 기반
TOCP: A Dataset for Chinese Profanity Processing
This paper introduced TOCP, a larger dataset of Chinese profanity. This dataset contains natural sentences collected from social media sites, the profane expressions appearing in the sentences, and their rephrasing sugge…
Sentence Rephrasing for Parsing Sentences with OOV Words
This paper addresses the problems of out-of-vocabulary (OOV) words, named entities in particular, in dependency parsing. The OOV words, whose word forms are unknown to the learning-based parser, in a sentence may decreas…
Dependency ParsingDomain AdaptationInformation RetrievalMachine Translation+3PERL: Pinyin Enhanced Rephrasing Language Model for Chinese ASR N-best Error Correction
ASR correction methods have predominantly focused on general datasets and have not effectively utilized Pinyin information, unique to the Chinese language. In this study, we address this gap by proposing a Pinyin Enhance…
Language ModelingLanguage ModellingRaply: A profanity-mitigated rap generator
The task of writing rap is challenging and involves producing complex rhyming schemes, yet meaningful lyrics. In this work, we propose Raply, a fine-tuned GPT-2 model capable of producing meaningful rhyming text in the s…
Chinese Spelling Correction as Rephrasing Language Model
This paper studies Chinese Spelling Correction (CSC), which aims to detect and correct the potential spelling errors in a given sentence. Current state-of-the-art methods regard CSC as a sequence tagging task and fine-tu…
Language ModelingLanguage ModellingmodelSentence+1