Sparse cepstral codes and power scale for instrument identification
Journal
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISBN
9781479928927
Date Issued
2014-01-01
Author(s)
Abstract
This paper presents a novel feature representation called sparse cepstral codes for instrument identification. We first motivate the approach by discussing why cepstrum is suitable for instrument identification. Then we propose the use of sparse coding and power normalization to derive compact codes that better represent the information of the cepstrum. Our evaluation on both uni-source and multi-source instrument identification tasks show that the proposed feature leads to significantly better accuracy than existing methods. We further show that cepstrum obtained from power-scaled spectrum can do better than typical cepstrum especially in multi-source signal. The proposed system achieves 0.955 F-score in uni-source dataset and 0.688 F-score in multi-source dataset. © 2014 IEEE.
Subjects
cepstrum | dictionary learning | instrument identification | power scale | sparse coding
Type
conference paper