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Voice Recognition for Periodontal Probing Medical Records under Korean-English Bilingual Conditions: A Feasibility Study

Authors
 Kim, Young Woo  ;  Kook, Jin Hyeok  ;  Choi, Yiseul  ;  Park, Wonse 
Citation
 HEALTHCARE INFORMATICS RESEARCH, Vol.32(2) : 118-124, 2026-04 
Journal Title
HEALTHCARE INFORMATICS RESEARCH
ISSN
 2093-3681 
Issue Date
2026-04
Keywords
Voice Recognition ; Natural Language Processing ; Electronic Health Records ; Dentistry ; Multilingualism
Abstract
Objectives: This study evaluated the feasibility of voice recognition-based electronic medical record (EMR) documentation for periodontal probing in dentistry, particularly emphasizing Korean-English bilingual speech patterns and real-world clinical conditions. Methods: Experiments were conducted in a dental chair setting during routine clinical hours. Environmental noise levels were measured, and two microphone types (stationary and pin-type) were evaluated. Periodontal probing phrases composed of three-digit numbers and positional terms were used for speech recognition. Consistent with common clinical practice in Korea, numerical values were spoken in Korean, whereas positional terms were spoken in English. Two speech-to-text application programming interfaces, Google Cloud Speech-to-Text and Naver Clova Speech Recognition, were assessed. Recognition accuracy was evaluated for both numerical components and complete bilingual phrases. Results: The mean environmental noise level was 60.65 dB and was minimally influenced by activity at adjacent dental chairs. The stationary microphone failed to capture speech effectively, whereas the pin-type microphone demonstrated stable recognition performance. For three-digit number recognition, accuracy was 88.3% with Google and 96.8% with Naver. For full-phrase recognition, complete matching was achieved in 36.7% of cases for Google and 52.5% for Naver. Partial recognition occurred more frequently for numerical components than for English positional terms. Conclusions: Voice recognition-based EMR documentation for periodontal probing demonstrated preliminary feasibility in a dental clinical environment; however, performance was influenced by Korean-English bilingual speech patterns. These findings suggest that bilingual speech characteristics should be considered when implementing voice recognition systems in dental EMR workflows. Further optimization is required before routine clinical application.
Files in This Item:
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DOI
10.4258/hir.2026.32.2.118
Appears in Collections:
2. College of Dentistry (치과대학) > Dept. of Advanced General Dentistry (통합치의학과) > 1. Journal Papers
Yonsei Authors
Park, Wonse(박원서) ORCID logo https://orcid.org/0000-0002-2081-1156
Choi, Yiseul(최이슬)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/212677
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