STCP: Simplified-Traditional Chinese Conversion and Proofreading
This paper aims to provide an effective tool for conversion between Simplified Chinese and Traditional Chinese. We present STCP, a customizable system comprising statistical conversion model, and proofreading web interface. Experiments show that our system achieves comparable character-level conversion performance with the state-of-art systems. In addition, our proofreading interface can effectively support diagnostics and data annotation. STCP is available at \url{http://lagos.lti.cs.cmu.edu:8002/}
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
2kenize: Tying Subword Sequences for Chinese Script Conversion
Simplified Chinese to Traditional Chinese character conversion is a common preprocessing step in Chinese NLP. Despite this, current approaches have poor performance because they do not take into account that a simplified…
General ClassificationTopic ClassificationVisTCP: A Visualization Framework to Construct Knowledge-Graph-Based Representation for Traditional Chinese Painting
Structured representation can characterize semantic objects and relationships in images. It provides a possible effective way for the semantic understanding of Traditional Chinese Paintings (TCPs) to better support archa…
Dual Long Short-Term Memory Networks for Sub-Character Representation Learning
Characters have commonly been regarded as the minimal processing unit in Natural Language Processing (NLP). But many non-latin languages have hieroglyphic writing systems, involving a big alphabet with thousands or milli…
Chinese Word SegmentationRepresentation LearningSegmentationCharacterizing Bias: Benchmarking Large Language Models in Simplified versus Traditional Chinese
While the capabilities of Large Language Models (LLMs) have been studied in both Simplified and Traditional Chinese, it is yet unclear whether LLMs exhibit differential performance when prompted in these two variants of …
Benchmarking