Mark Cartwright, Bryan Pardo, Andy Sabin, Bongjun Kim


SocialEQ is a web-based project for learning a vocabulary of actionable audio equalization descriptors. These descriptors can be used to determine what descriptors people tend to agree upon, what descriptors are actionable by an audio equalizer, and consequently which descriptors need to be taught by a user. This data has been used to create audio production interfaces that respond to descriptive language, and has also been used to translate difficult to define descriptors to other languages.

Related Papers

[pdf] [poster] Cartwright, M., Pardo, B. Translating Sound Adjectives by Collectively Teaching Abstract Representations. In Proceedings of the Collective Intelligence Conference, 2014.

[pdf] Cartwright, M., Pardo, B. Social-EQ: Crowdsourcing an Equalization Descriptor Map. In Proceedings of the International Society for Music Information Retreival Conference (ISMIR), 2013.


SocialEQ dataset