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Development of an Open-Source–Based AI Speech-to-Text System and Performance Analysis Using Presidential Speech

  • Journal of Korean Society of Archives and Records Management
  • Abbr : JRMASK
  • 2025, 25(3), pp.243~258
  • DOI : 10.14404/JKSARM.2025.25.3.243
  • Publisher : Korean Society of Archives and Records Management
  • Research Area : Interdisciplinary Studies > Library and Information Science > Archival Studies / Conservation
  • Received : July 15, 2025
  • Accepted : August 22, 2025
  • Published : August 31, 2025

Bae Minsoo 1 Yu Young-Moon 2

1대통령기록관 공업연구사
2대통령기록관 공업연구관

Accredited

ABSTRACT

This study developed an open-source–based AI Speech-to-Text (STT) system and analyzed its performance by applying it to presidential speech. While various high-performance STT services are currently commercialized, most are provided online for a fee. However, because of the nature of presidential records, using online services can raise security concerns, and incurring continuous costs for processing accumulating records is inefficient. To address this, the Presidential Archives has developed an offline STT system based on open-source AI models, which is currently under testing and operation. In this study, approximately three hours of presidential audiovisual records were transcribed into text using this function, and the error rate was measured by comparing with the actual text. The results showed that the overall performance is comparable to the latest commercial online services. Additionally, speech rate and recording quality were extracted and analyzed for their correlation with the error rate. Finally, this research highlights the feasibility of applying open-source AI technologies for the utilization of records.

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