When users attend the same public event, there may be multiple audiovisual recordings that are then posted on social media and websites. The availability of such a massive amount of user-generated recordings (UGR) has triggered new research directions related to the search, organization, and management of this content. And it has provided inspiration for new business models for content storage, retrieval, and consumption. The authors propose an approach to combine the available recordings based on a normalization step and a mixing step. The normalization step defines a fixed-with-time gain that is specific to each UGR. In the mixing step, a mechanism that reduces the master gain in accordance with the number of activated inputs at each time is employed. An approach called orthogonal mixing is presented, which is based on the assumption that the mixture components are mutually independent. The presented mixing process allows the combination of multiple short-duration UGRs to produce a longer audio stream, with potentially better quality than any one of its constituent parts. This property is exploited in the design of an automatic mixing process that exploits all the available audio recordings at each moment. Automatic mixing is then possible.
https://www.aes.org/e-lib/browse.cfm?elib=20452
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