Rich Semantic Knowledge Enhanced Large Language Models for Few-shot Chinese Spell Checking

arXiv:2403.08492v1 Announce Type: new
Abstract: Chinese Spell Checking (CSC) is a widely used technology, which plays a vital role in speech to text (STT) and optical character recognition (OCR). Most of the existing CSC approaches relying on BERT architecture achieve excellent performance. However, limited by the scale of the foundation model, BERT-based method does not work well in few-shot scenarios, showing certain limitations in practical applications. In this paper, we explore using an in-context learning method named RS-LLM (Rich Semantic …

abstract architecture arxiv bert character recognition chinese cs.cl few-shot however knowledge language language models large language large language models ocr optical optical character recognition performance recognition role scale semantic speech spell technology text type vital