As the interest in large language models grows, the importance of accuracy in automatic speech recognition has become more pronounced. This is especially true for lectures that include specialized terminology. In such cases, the success rate of traditional ASR models tends to be low, presenting a significant challenge. A method using the word frequency difference approach has been proposed to improve ASR performance for specialized terminology. We investigated this proposal through experiments and data analysis to determine if it effectively addresses the issue. In addition, we introduced the power law as the theoretical foundation for the relative frequency methodology mentioned in this approach.

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