Handbook of Multimedia for Digital Entertainment and Arts- P26: The advances in computer entertainment, multi-player and online games, technology-enabled art, culture and performance have created a new form of entertainment and art, which attracts and absorbs their participants. The fantastic success of this new field has influenced the development of the new digital entertainment industry and related products and services, which has impacted every aspect of our lives. | 756 M. Fink et al. Within-Query Consistency Once the query frames are individually matched to the audio database using the efficient hashing procedure the potential matches are validated. Simply counting the number of frame matches is inadequate since a database snippet might have many frames matched to the query snippet but with completely wrong temporal structure. To insure temporal consistency each hit is viewed as support for a match at a specific query-to-database offset. For example if the eighth descriptor q8 in the 5-s 415-frame-long Seinfeld query snippet q hits the 1 008th database descriptor x1 008 this supports a candidate match between the 5-s query and frames 1 001 through 1 415 in the database. Other matches mapping qn to x1 000 n 1 n 415 would support this same candidate match. In addition to temporal consistency we need to account for frames when conversations temporarily drown out the ambient audio. We use the model of interference from 7 that is as an exclusive switch between ambient audio and interfering sounds. For each query frame i there is a hidden variable y - if y - 0 the ith frame of the query is modeled as interference only if y - 1 the i th frame is modeled as from clean ambient audio. Taking this extreme view pure ambient or pure interference is justified by the extremely low precision with which each audio frame is represented 32 bits and is softened by providing additional bit-flip probabilities for each of the 32 positions of the frame vector under each of the two hypotheses y 0 and y - 1 . Finally the frame transitions between ambient-only and interference-only states are treated as a hidden first-order Markov process with transition probabilities derived from training data. We re-used the 66-parameter probability model given by Ke et al. 7 . In summary the final model of the match probability between a query vector q and an ambient-database vector with an offset of N frames xN is 415 P q xN Y P hq XN ly P y ly -i n 1 where qn xm .
