@inproceedings{d250a28afc9d414598095d519c5ad189,
title = "Objective characterization of audio signal quality: Applications to music collection description",
abstract = "In this paper, we propose a set of audio features to describe the quality of an audio signal. Audio quality is here considered as being modified by the chain of processes/effects applied to the individual instrument tracks to obtain the final mix of a musical piece. Thus, the quality also depends on the mastering processes applied to the final mix or the signal degradation caused by MP3 compression. To evaluate our proposal, we created a large set of artificial mixes and also used real-world studio mixes. Using unsupervised and supervised classification methods, we show that our proposed audio features can detect the processing chain. Since this processing chain applied in professional studio has evolved over the years, we use our audio features to directly predict the decade during which a music track was recorded.",
keywords = "audio quality, audio reverse-engineering, database indexing, music information retrieval, music remixing",
author = "Dominique Fourer and Geoffroy Peeters",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 ; Conference date: 05-03-2017 Through 09-03-2017",
year = "2017",
month = jun,
day = "16",
doi = "10.1109/ICASSP.2017.7952248",
language = "English",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "711--715",
booktitle = "2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings",
}