Our company, which provides services utilizing speech recognition, recognizes the accuracy of speech recognition as essential for successful service deployment. While there are numerous methods to correct speech recognition results, this study focuses on scoring N-best hypotheses generated by a speech recognition model using large language models (LLMs) to correct Japanese speech recognition results. The scoring process demonstrated improvements in both WER (Word Error Rate) and CER (Character Error Rate).