Document Type
Conference Proceeding
Language
eng
Format of Original
4 p.
Publication Date
5-14-2006
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Source Publication
2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings (Volume:1 )
Source ISSN
1520-6149
Original Item ID
DOI: 10.1109/ICASSP.2006.1660005
Abstract
This paper introduces the Greenwood function cepstral coefficient (GFCC) and generalized perceptual linear prediction (GPLP) feature extraction models for the analysis of animal vocalizations across arbitrary species. These features are generalizations of the well-known mel-frequency cepstral coefficient (MFCC) and perceptual linear prediction (PLP) approaches, tailored to take optimal advantage of available knowledge of each species' auditory frequency range and/or audiogram data. Illustrative results are presented comparing use of the GFCC and GPLP features versus MFCC features over the same frequency ranges
Recommended Citation
Clemins, Patrick J., "Generalized Perceptual Features for Vocalization Analysis across Multiple Species" (2006). Electrical and Computer Engineering Faculty Research and Publications. 145.
https://epublications.marquette.edu/electric_fac/145
Comments
Accepted version. Published as part of the proceedings of the conference, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings (Volume:1 ); I-253 - I-256. DOI. © 2019 IEEE. Used with permission.