Acoustic Surveillance of Hazardous Situations Using Nonnegative Matrix Factorization and Hidden Markov Model

Jeon KM, Lee DY, Kim HK, Lee MJ. Acoustic Surveillance of Hazardous Situations Using Nonnegative Matrix Factorization and Hidden Markov Model. In: AES Convention 137. Audio Engineering Society; 2014. Paper 9203. Available from: https://aes.org/publications/elibrary-page/?id=17526

@inproceedings{Jeon2014_17526,
  author = {Jeon, Kwang Myung and Lee, Dong Yun and Kim, Hong Kook and Lee, Myung J.},
  title = {{Acoustic Surveillance of Hazardous Situations Using Nonnegative Matrix Factorization and Hidden Markov Model}},
  booktitle = {AES Convention 137},
  note = {Paper 9203},
  year = {2014},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=17526}
}

TY  - CPAPER
TI  - Acoustic Surveillance of Hazardous Situations Using Nonnegative Matrix Factorization and Hidden Markov Model
AU  - Jeon, Kwang Myung
AU  - Lee, Dong Yun
AU  - Kim, Hong Kook
AU  - Lee, Myung J.
T2  - AES Convention 137
M1  - Paper 9203
PY  - 2014
DA  - 2014/10/06
UR  - https://aes.org/publications/elibrary-page/?id=17526
PB  - Audio Engineering Society
LA  - en
AB  - In this paper an acoustic surveillance method is proposed for accurately detecting hazardous situations under noisy conditions. In order to improve detection accuracy, the proposed method first tries to separate each atypical event from the input noisy audio signal. Next, maximum likelihood classification using multiple hidden Markov models (HMMs) is carried out to decide whether or not an atypical event occurs. Performance evaluation shows that the proposed method achieves higher detection accuracy under various signal-to-noise ratio (SNR) conditions than a conventional HMM-based method.
ER  -