A Robust Audio Feature Extraction Algorithm for Music Identification

Bourguet ML, Wang J. A Robust Audio Feature Extraction Algorithm for Music Identification. In: AES Convention 129. Audio Engineering Society; 2010.pp. 8180:1-7. Available from: https://aes.org/publications/elibrary-page/?id=15603

@inproceedings{Bourguet2010_15603,
  author = {Bourguet, Marie-Luce and Wang, Jiajun},
  title = {{A Robust Audio Feature Extraction Algorithm for Music Identification}},
  booktitle = {AES Convention 129},
  pages = {8180:1-7},
  url = {https://aes.org/publications/elibrary-page/?id=15603},
  year = {2010},
  month = nov,
  publisher = {Audio Engineering Society}
}

TY  - CPAPER
TI  - A Robust Audio Feature Extraction Algorithm for Music Identification
AU  - Bourguet, Marie-Luce
AU  - Wang, Jiajun
T2  - AES Convention 129
SP  - 1
EP  - 7
M1  - Paper 8180
PY  - 2010
DA  - 2010/11/06
UR  - https://aes.org/publications/elibrary-page/?id=15603
PB  - Audio Engineering Society
LA  - en
AB  - In this paper, we describe a novel audio feature extraction method, which can effectively improve the performance of music identification under noisy circumstances. It is based on a dual box approach that extracts from the sound spectrogram point clusters with significant energy variation. This approach was tested in a song finder application that can identify music from samples recorded by microphone in the presence of dominant noise. A series of experiments show that under noisy circumstances, our system outperforms current state-of-the-art music identification algorithms and provides very good precision, scalability and query efficiency.
ER  -