Automatic Detection of Audio Problems for Quality Control in Digital Music Distribution

Alonso-Jiménez P, Joglar-Ongay L, Serra X, Bogdanov D. Automatic Detection of Audio Problems for Quality Control in Digital Music Distribution. In: AES Convention 146. Audio Engineering Society; 2019. Paper 10205. Available from: https://aes.org/publications/elibrary-page/?id=20338

@inproceedings{AlonsoJimenez2019_20338,
  author = {Alonso-Jiménez, Pablo and Joglar-Ongay, Luis and Serra, Xavier and Bogdanov, Dmitry},
  title = {{Automatic Detection of Audio Problems for Quality Control in Digital Music Distribution}},
  booktitle = {AES Convention 146},
  note = {Paper 10205},
  year = {2019},
  month = mar,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=20338}
}

TY  - CPAPER
TI  - Automatic Detection of Audio Problems for Quality Control in Digital Music Distribution
AU  - Alonso-Jiménez, Pablo
AU  - Joglar-Ongay, Luis
AU  - Serra, Xavier
AU  - Bogdanov, Dmitry
T2  - AES Convention 146
M1  - Paper 10205
PY  - 2019
DA  - 2019/03/06
UR  - https://aes.org/publications/elibrary-page/?id=20338
PB  - Audio Engineering Society
LA  - en
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.
ER  -