X. Yang, Z. Wen, G. Ren, and M. F. Bocko, “Media Content Emphasis Using Audio Effect Contrasts: Building Quantitative Models from Subjective Evaluations,” in Proc. AES Convention 135, Oct. 2013, Paper 9017. [Online]. Available: https://aes.org/publications/elibrary-page/?id=17065
Yang X, Wen Z, Ren G, Bocko MF. Media Content Emphasis Using Audio Effect Contrasts: Building Quantitative Models from Subjective Evaluations. In: AES Convention 135. Audio Engineering Society; 2013. Paper 9017. Available from: https://aes.org/publications/elibrary-page/?id=17065
@inproceedings{Yang2013_17065,
author = {Yang, Xuchen and Wen, Zhe and Ren, Gang and Bocko, Mark F.},
title = {{Media Content Emphasis Using Audio Effect Contrasts: Building Quantitative Models from Subjective Evaluations}},
booktitle = {AES Convention 135},
note = {Paper 9017},
year = {2013},
month = oct,
publisher = {Audio Engineering Society},
url = {https://aes.org/publications/elibrary-page/?id=17065}
}
TY - CPAPER
TI - Media Content Emphasis Using Audio Effect Contrasts: Building Quantitative Models from Subjective Evaluations
AU - Yang, Xuchen
AU - Wen, Zhe
AU - Ren, Gang
AU - Bocko, Mark F.
T2 - AES Convention 135
M1 - Paper 9017
PY - 2013
DA - 2013/10/06
UR - https://aes.org/publications/elibrary-page/?id=17065
PB - Audio Engineering Society
LA - en
AB - In this paper we study media content emphasis patterns of audio effects and construct their quantitative models using subjective evaluation experiments. The media content emphasis patterns are produced by contrasts between effect-sections and non-effect sections, which change the focus of audience attention. We investigate media emphasis patterns of typical audio effects including equalization, reverberation, dynamic range control, and chorus. We compile audio test samples by applying different settings of audio effects and their permutations. Then we construct quantitative models based on the audience rating of the “subjective significance” of test audio segments. Statistical experiment design and analysis techniques are employed to establish the statistical significance of our proposed models.
ER -