A Robust and Computationally Efficient Speech/Music Discriminator

Barbedo JGA, Lopes A. A Robust and Computationally Efficient Speech/Music Discriminator. J Audio Eng Soc. 2006;54(7/8):571-588. Available from: https://aes.org/publications/elibrary-page/?id=13897

@article{Barbedo2006_13897,
  author = {Barbedo, Jayme Garcia Arnal and Lopes, Amauri},
  title = {{A Robust and Computationally Efficient Speech/Music Discriminator}},
  journal = {Journal of the Audio Engineering Society},
  volume = {54},
  number = {7/8},
  pages = {571--588},
  year = {2006},
  month = jul,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=13897}
}

TY  - JOUR
TI  - A Robust and Computationally Efficient Speech/Music Discriminator
AU  - Barbedo, Jayme Garcia Arnal
AU  - Lopes, Amauri
T2  - Journal of the Audio Engineering Society
J2  - J. Audio Eng. Soc.
VL  - 54
IS  - 7/8
SP  - 571
EP  - 588
PY  - 2006
DA  - 2006/07/06
UR  - https://aes.org/publications/elibrary-page/?id=13897
PB  - Audio Engineering Society
LA  - en
AB  - A New method for discriminating between speech and music signals is introduced. The strategy is based on the extraction of four features, whose values are combined linearly into a unique parameter. This parameter is used to distinguish between the two kinds of signals. The method has achieved an accuracy superior to 99%, even for severely degraded and noisy signals. Moreover, the low dimensionality of the feature space, together with a very simple information-merging technique, has resulted in a remarkable robustness to new situations. The low computational complexity of the method makes it appropriate for applications that demand real-time operation. Finally excellent resolution for the segmentation of audio streams is achieved by manipulating the analyzed data properly.
ER  -