• Title/Summary/Keyword: Snoring Sound Classification

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Snoring Sound Classification using Efficient Spectral Features and SVM for Smart Pillow (스마트 베개를 위한 효율적인 스펙트럼 특징과 SVM을 이용한 코골이 판별 방법)

  • Kim, Byeong Man;Moon, Chang Bae
    • Journal of Korea Society of Industrial Information Systems
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    • v.23 no.2
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    • pp.11-18
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    • 2018
  • Severe snoring can lead to OSA(Obstructive Sleep Apnea), which can lead to life-threatening cases, and snoring can lead to serious pernicious relationships. In order to solve these snoring problems, several types of smart pillows have recently been released. The core technology is snoring discrimination technology, ie, a technique for determining whether snoring is included in the input sound. In this paper, we propose a snoring detection method to apply to a smart pillow. After extracting the features of the snoring sound from the input signal, we discriminate the snoring using these features and SVM. In order to measure the performance of the proposed method, comparative experiments with the existing methods are performed. The experimental results show about 6% better discrimination performance than the existing method.