  As the interest in large language models grows, the importance of accuracy in
automatic speech recognition has become more pronounced. This is particularly
true for lectures that include specialized terminology, where the success rate
of traditional ASR models tends to be low, posing a challenging problem. A
method to improve ASR performance for specialized terminology using the word
frequency difference approach has been proposed. Through experiments and data
analysis, we investigated whether this proposal effectively addressed this
issue. In addition, we introduced the power law as the theoretical foundation
for the relative frequency methodology mentioned in this approach.
