Sound quality and spatial sound have been topics of research for decades in relation to loudspeakers and headphones as well as performance spaces (e.g., concert halls). Attributes may be used as a means to characterize sound quality through listening tests. Attribute development protocols are well reported and have been employed to a wide range of spatial sound applications. However, the usage of attribute often leads to researchers discussing the merits of the attributes as opposed to focusing upon the object of the research. Over the last few decades a large number of articles have included the development of a spatial sound attribute. This paper describes the collection of many known research articles on spatial sound attributes from a wide range of domains. As opposed to repeating traditional word elicitation and group discussion, we have chosen to use a semantic text data mining approach to find common attribute meanings, which is then followed by a sorting and refinement process with expert assessors. This process is defined in detail and the results of the semantic text mining are presented as part of the further development of a sound wheel for sound reproduction.
Click to purchase paper as a non-member or you can login as an AES member to see more options.
No AES members have commented on this paper yet.
To be notified of new comments on this paper you can
subscribe to this RSS feed.
Forum users should login to see additional options.
If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.
