Audio events detection based highlights extraction from baseball, golf and soccer games in a unified framework

We developed a unified framework to extract highlights from three sports: baseball, golf and soccer by detecting some of the common audio events that are directly indicative of highlights. We used MPEG-7 audio features and entropic prior hidden Markov models (HMM) as the audio features and classifier respectively to recognize these common audio events. Together with pre- and post-processing techniques using general sports knowledge, we have been able to generate promising results dealing with the audio track that is dominated by audio mixtures and noisy background.