Investigation of Wavelet Approaches for Joint Temporal, Spectral and Cepstral Features in Audio Semantics

Dimoulas CA, Kalliris GM. Investigation of Wavelet Approaches for Joint Temporal, Spectral and Cepstral Features in Audio Semantics. In: AES Convention 134. Audio Engineering Society; 2013. Paper 8858. Available from: https://aes.org/publications/elibrary-page/?id=16759

@inproceedings{Dimoulas2013_16759,
  author = {Dimoulas, Charalampos A. and Kalliris, George M.},
  title = {{Investigation of Wavelet Approaches for Joint Temporal, Spectral and Cepstral Features in Audio Semantics}},
  booktitle = {AES Convention 134},
  note = {Paper 8858},
  year = {2013},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=16759}
}

TY  - CPAPER
TI  - Investigation of Wavelet Approaches for Joint Temporal, Spectral and Cepstral Features in Audio Semantics
AU  - Dimoulas, Charalampos A.
AU  - Kalliris, George M.
T2  - AES Convention 134
M1  - Paper 8858
PY  - 2013
DA  - 2013/05/06
UR  - https://aes.org/publications/elibrary-page/?id=16759
PB  - Audio Engineering Society
LA  - en
AB  - The current paper focuses on the investigation of wavelet approaches for joint time, frequency, and cepstral audio feature extraction. Wavelets have been thoroughly studied over the last decades as an alternative signal analysis approach. Wavelet-features have also been successfully implemented in a variety of pattern recognition applications, including audio semantics. Recently, wavelet-adapted mel-frequency cepstral coefficients have been proposed as applicable features in speech recognition and general audio classification, incorporating perceptual attributes. In this context, various wavelet configuration-schemes are examined for wavelet-cepstral audio features extraction. Additional wavelet parameters are utilized in the formation of wavelet-feature-vectors and evaluated in terms of salient feature ranking. Comparisons with classical time-frequency and cepstral audio features are conducted in typical audio-semantics scenarios.
ER  -