AES E-Library

AL. Alonso-Jimé, P. nez, L. Joglar-Ongay, and X. Serra, D. Bogdanov, "Automatic Detection of Audio Problems for Quality Control in Digital Music Distribution," Paper 10205, (2019 March.). doi: AL. Alonso-Jimé, P. nez, L. Joglar-Ongay, and X. Serra, D. Bogdanov, "Automatic Detection of Audio Problems for Quality Control in Digital Music Distribution," Paper 10205, (2019 March.). doi:
Abstract: Providing contents within the industry quality standards is crucial for digital music distribution companies. For this reason an excellent quality control (QC) support is paramount to ensure that the music does not contain audio defects. Manual QC is a very effective and widely used method, but it is very time and resources consuming. Therefore, automation is needed in order to develop an efficient and scalable QC service. In this paper we outline the main needs to solve together with the implementation of digital signal processing algorithms and perceptual heuristics to improve the QC workflow. The algorithms are validated on a large music collection of more than 300,000 tracks.

@article{alonso-jimé2019automatic,
author={alonso-jimé and nez, pablo and joglar-ongay, luis and serra, xavier and bogdanov, dmitry},
journal={journal of the audio engineering society},
title={automatic detection of audio problems for quality control in digital music distribution},
year={2019},
volume={},
number={},
pages={},
doi={},
month={march},} @article{alonso-jimé2019automatic,
author={alonso-jimé and nez, pablo and joglar-ongay, luis and serra, xavier and bogdanov, dmitry},
journal={journal of the audio engineering society},
title={automatic detection of audio problems for quality control in digital music distribution},
year={2019},
volume={},
number={},
pages={},
doi={},
month={march},
abstract={providing contents within the industry quality standards is crucial for digital music distribution companies. for this reason an excellent quality control (qc) support is paramount to ensure that the music does not contain audio defects. manual qc is a very effective and widely used method, but it is very time and resources consuming. therefore, automation is needed in order to develop an efficient and scalable qc service. in this paper we outline the main needs to solve together with the implementation of digital signal processing algorithms and perceptual heuristics to improve the qc workflow. the algorithms are validated on a large music collection of more than 300,000 tracks.},}

TY - paper
TI - Automatic Detection of Audio Problems for Quality Control in Digital Music Distribution
SP - EP -
AU - Alonso-Jimé
AU - nez, Pablo
AU - Joglar-Ongay, Luis
AU - Serra, Xavier
AU - Bogdanov, Dmitry
PY - 2019
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - March 2019 TY - paper
TI - Automatic Detection of Audio Problems for Quality Control in Digital Music Distribution
SP - EP -
AU - Alonso-Jimé
AU - nez, Pablo
AU - Joglar-Ongay, Luis
AU - Serra, Xavier
AU - Bogdanov, Dmitry
PY - 2019
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - March 2019
AB - Providing contents within the industry quality standards is crucial for digital music distribution companies. For this reason an excellent quality control (QC) support is paramount to ensure that the music does not contain audio defects. Manual QC is a very effective and widely used method, but it is very time and resources consuming. Therefore, automation is needed in order to develop an efficient and scalable QC service. In this paper we outline the main needs to solve together with the implementation of digital signal processing algorithms and perceptual heuristics to improve the QC workflow. The algorithms are validated on a large music collection of more than 300,000 tracks.