Automatic attendance rating of movie content using bag of audio words representation

The sensory experience of watching a movie, links input from both sight and hearing modalities. Yet traditionally, the motion picture rating system largely relies on the visual content of the film, to make its informed decisions to parents. The current rating process is fairly elaborate. It requires a group of parents to attend a full screening, manually prepare and submit their opinions, and vote out the appropriate audience age for viewing. Rather, our work explores the feasibility of classifying age attendance of a movie automatically, resorting to solely analyzing the movie auditory data. Our high performance software records the audio content of the shorter movie trailer, and builds a labeled training set of original and artificially distorted clips. We use a bag of audio words to effectively represent the film sound track, and demonstrate robust and closely correlated classification accuracy, in exploiting boolean discrimination and ranked retrieval methods.