Supervised Machine Learning for Quality Assurance in Loudspeakers: Time Distortion Analysis

O'Donnell G. Supervised Machine Learning for Quality Assurance in Loudspeakers: Time Distortion Analysis. In: Express Paper. Audio Engineering Society; 2025. Paper 349. Available from: https://aes.org/publications/elibrary-page/?id=22900

@inproceedings{ODonnell2025_22900,
  author = {O'Donnell, Gregg},
  title = {{Supervised Machine Learning for Quality Assurance in Loudspeakers: Time Distortion Analysis}},
  note = {Paper 349},
  year = {2025},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=22900}
}

TY  - CPAPER
TI  - Supervised Machine Learning for Quality Assurance in Loudspeakers: Time Distortion Analysis
AU  - O'Donnell, Gregg
M1  - Paper 349
PY  - 2025
DA  - 2025/05/12
UR  - https://aes.org/publications/elibrary-page/?id=22900
PB  - Audio Engineering Society
LA  - en
AB  - Measuring a speakers ability to respond to an instantaneous pulse of energy will result in distortion at its output. Factors such as speaker geometry, material properties, equipment error, and the conditions of the environment will create artifacts within the captured data. This paper explores the extraction of time-domain features from these responses, and the training of a predictive model to allow for classification and rapid quality assurance.
ER  -