Optimally selecting types of audio to align with a particular experience is a difficult task. Many venues hire music curation service providers, such as DJs, which can be prohibitively expensive. Further, a hired music curator that incorrectly curates music for a venue can substantially reduce patronage to a venue. Finally, it can be prohibitively difficult to determine whether music is being curated incorrectly or if patronage in a venue is being reduced due to some other cause. A music curation service provider’s task is complicated by rapidly changing tastes in music within the general public. This problem is exacerbated due to the limited information available to music curation service providers. Specifically, music curation service providers have limited information to determine whether curated musical selections are inducing a desired effect (e.g., dancing, etc.). For example, a music curation service provider selecting music in real-time for a dance club can only subjectively examine a crowd to determine a preference towards music being played based on actions being taken by the crowd (e.g., singing, dancing, moving to a certain part of the venue, etc.).

Accordingly, the following disclosure proposes optimizing audio curation for venues based on real-time analysis of user response. Specifically, a computing system accessible by a venue, or music curation service provider, can receive user data from users located within a particular venue. User data can include sensor data (e.g., accelerometer data, Inertial Measurement Unit (IMU) data, etc.), location data, contextual information (e.g., reviews provided by the user, media captured by the user, etc.), or any other type of data that can be analyzed to determine a user response. Based on the user data, the computing system can determine an aggregate response from users located within the venue (e.g., a highly positive response, a mildly negative response, etc.). This positive aggregate response can be indicated to a venue, or a music curation service provider associated with the venue, so that music curation can be adjusted in real-time based on the aggregate user response. Alternatively, the computing system can automatically provide music curation services based on the aggregate user response. In such fashion, inefficiencies with conventional music curation techniques can be reduced, and/or eliminated.

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