Automatic sound recognition for the hearing impaired

In Chul Yoo, Dongsuk Yook

Research output: Contribution to journalArticlepeer-review

35 Citations (Scopus)


We present a wearable sound recognition system to assist the hearing impaired. Traditionally, hearing aid dogs are specially trained to facilitate the daily life of the hearing impaired. However, since training hearing aid dogs is costly and time-consuming, it would be desirable to substitute them with an automatic sound recognition system using speech recognition technologies. As the sound recognition system will be used in home environments where background noises and reverberations are high, conventional speech recognition techniques are not directly applicable, since their performance drops off rapidly in these environments. In this paper, we introduce a new sound recognition algorithm which is optimized for mechanical sounds such as doorbells. The new algorithm uses a new distance measure called the normalized peak domination ratio (NPDR) that is based on the characteristic spectral peaks of these sounds. The proposed algorithm showed a sound recognition accuracy of 99.7%, and noise rejection accuracy of 99.7%.

Original languageEnglish
Pages (from-to)2029-2036
Number of pages8
JournalIEEE Transactions on Consumer Electronics
Issue number4
Publication statusPublished - 2008

Bibliographical note

Funding Information:
1This work was supported by the MKE (Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITA (Institute for Information Technology Advancement) (IITA-2008-C1090-0803-0006).


  • Acoustic fingerprint
  • Acoustic scene analysis
  • Auditory system
  • Dogs
  • Euclidean distance
  • Noise
  • Noise measurement
  • Signal to noise ratio
  • Sound recognition
  • Spectral peak
  • Speech recognition

ASJC Scopus subject areas

  • Media Technology
  • Electrical and Electronic Engineering


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