Abstract
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 language | English |
|---|---|
| Pages (from-to) | 2029-2036 |
| Number of pages | 8 |
| Journal | IEEE Transactions on Consumer Electronics |
| Volume | 54 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 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).
Keywords
- 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