Enhancing ASR Performance through OCR Word Frequency Analysis: Theoretical Foundations
<|reference_start|>Enhancing ASR Performance through OCR Word Frequency Analysis: Theoretical Foundations: 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.<|reference_end|>
@article{jung2024enhancing,
    title={Enhancing ASR Performance through OCR Word Frequency Analysis:
  Theoretical Foundations},
    author={Kyudan Jung, Nam-Joon Kim, Hyun Gon Ryu, Hyuk-Jae Lee},
    journal={arXiv preprint arXiv:2405.02995},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.02995},
    primaryClass={math.NA cs.NA cs.SD}
}