G. Ramos and J. J. Lopez, “Subjective Evaluation of an Equalization Method for Loudspeakers Based on Random Parametric Optimization of IIR Filters,” in Proc. AES Convention 116, May 2004, Paper 6081. [Online]. Available: https://aes.org/publications/elibrary-page/?id=12706
Ramos G, Lopez JJ. Subjective Evaluation of an Equalization Method for Loudspeakers Based on Random Parametric Optimization of IIR Filters. In: AES Convention 116. Audio Engineering Society; 2004. Paper 6081. Available from: https://aes.org/publications/elibrary-page/?id=12706
@inproceedings{Ramos2004_12706,
author = {Ramos, German and Lopez, Jose Javier},
title = {{Subjective Evaluation of an Equalization Method for Loudspeakers Based on Random Parametric Optimization of IIR Filters}},
booktitle = {AES Convention 116},
note = {Paper 6081},
year = {2004},
month = may,
publisher = {Audio Engineering Society},
url = {https://aes.org/publications/elibrary-page/?id=12706}
}
TY - CPAPER
TI - Subjective Evaluation of an Equalization Method for Loudspeakers Based on Random Parametric Optimization of IIR Filters
AU - Ramos, German
AU - Lopez, Jose Javier
T2 - AES Convention 116
M1 - Paper 6081
PY - 2004
DA - 2004/05/06
UR - https://aes.org/publications/elibrary-page/?id=12706
PB - Audio Engineering Society
LA - en
AB - In this paper a subjective evaluation of a novel method for loudspeaker equalization is presented. The equalization is performed using a direct method with random parametric optimization for the design of a bank of second order peak filters, RaPOSOS. The subjective evaluation has been carried out using a preselected jury composed by lecturers, research staff and university students related with audio engineering. For evaluating its performance, it has been compared with other well known equalization method using the ABX test. In particular, our method with different level of approximation has been compared with long FIR filters obtained by minimum square error criteria. The results show that with relatively low order filters, the perceived difference is anecdotic or inexistent, requiring quite less computational cost.
ER -