Automatic Soundscape Affect Recognition Using A Dimensional Approach

Fan J, Thorogood M, Pasquier P. Automatic Soundscape Affect Recognition Using A Dimensional Approach. J Audio Eng Soc. 2016;64(9):646-653. doi:10.17743/jaes.2016.0044

@article{Fan2016_18373,
  author = {Fan, Jianyu and Thorogood, Miles and Pasquier, Philippe},
  title = {{Automatic Soundscape Affect Recognition Using A Dimensional Approach}},
  journal = {Journal of the Audio Engineering Society},
  volume = {64},
  number = {9},
  pages = {646--653},
  year = {2016},
  month = sep,
  publisher = {Audio Engineering Society},
  doi = {10.17743/jaes.2016.0044},
  url = {https://doi.org/10.17743/jaes.2016.0044}
}

TY  - JOUR
TI  - Automatic Soundscape Affect Recognition Using A Dimensional Approach
AU  - Fan, Jianyu
AU  - Thorogood, Miles
AU  - Pasquier, Philippe
T2  - Journal of the Audio Engineering Society
J2  - J. Audio Eng. Soc.
VL  - 64
IS  - 9
SP  - 646
EP  - 653
PY  - 2016
DA  - 2016/09/06
DO  - 10.17743/jaes.2016.0044
UR  - https://doi.org/10.17743/jaes.2016.0044
PB  - Audio Engineering Society
LA  - en
AB  - Soundscape studies have demonstrated a variety of approaches for investigating how soundscapes affect is part of immersive experiences. This research tries to develop an automatic affect recognition system that soundscape composers can use to create emotional compositions to evoke a target mood. In addition, this system can offer sound designers a more streamlined workflow for creating suitable sound effects for films and can offer engineers a way to design mood-enabled recommendation systems for retrieval of soundscape recordings. This research uses ground truth data collected from an online survey, and an analysis of the corpus shows that participants have a high level of agreement on the valence and arousal of soundscapes. The authors then generated a gold standard by averaging user responses. The propose system obtained better results than an expert-user model.
ER  -