Sensory Profiling of High-End Loudspeakers Using Rapid Methods—Part 3: Check-All-That-Apply with Naïve Assessors

Hicks L, Moulin S, Bech S. Sensory Profiling of High-End Loudspeakers Using Rapid Methods—Part 3: Check-All-That-Apply with Naïve Assessors. J Audio Eng Soc. 2018;66(5):329-342. doi:10.17743/jaes.2018.0015

@article{Hicks2018_19564,
  author = {Hicks, Lucy and Moulin, Samuel and Bech, Søren},
  title = {{Sensory Profiling of High-End Loudspeakers Using Rapid Methods—Part 3: Check-All-That-Apply with Naïve Assessors}},
  journal = {Journal of the Audio Engineering Society},
  volume = {66},
  number = {5},
  pages = {329--342},
  year = {2018},
  month = may,
  publisher = {Audio Engineering Society},
  doi = {10.17743/jaes.2018.0015},
  url = {https://doi.org/10.17743/jaes.2018.0015}
}

TY  - JOUR
TI  - Sensory Profiling of High-End Loudspeakers Using Rapid Methods—Part 3: Check-All-That-Apply with Naïve Assessors
AU  - Hicks, Lucy
AU  - Moulin, Samuel
AU  - Bech, Søren
T2  - Journal of the Audio Engineering Society
J2  - J. Audio Eng. Soc.
VL  - 66
IS  - 5
SP  - 329
EP  - 342
PY  - 2018
DA  - 2018/05/06
DO  - 10.17743/jaes.2018.0015
UR  - https://doi.org/10.17743/jaes.2018.0015
PB  - Audio Engineering Society
LA  - en
AB  - Faster sensory profiling methods are gaining interest because they do not require a training phase and can be performed by trained or untrained assessors. As the 3rd article in a series, this paper considers the check-all-that-apply (CATA) method with high-end loudspeakers. A CATA question is a multiple-choice question where participants are presented with a list of descriptive attributes (words or phrases) and a product to be evaluated. Listeners are then asked to select all the attributes that they think apply to the product. A preliminary test was conducted with naïve assessors to reduce a list of possible attributes to a suitable number appropriate for a CATA question. A listening test was then conducted with naïve assessors using the CATA method, and two methods for characterizing the loudspeakers were explored using Correspondence Analysis (CA) and Hierarchical Cluster Analysis (HCA). CA produced bidimensional plots for each track, allowing characterization inferred from the positioning of loudspeakers and attributes. HCA provided four clusters of loudspeaker-track combinations, with attributes that best describe each cluster. The CATA method was able to produce discriminative and descriptive characterizations of the loudspeakers.
ER  -