Spotting events in continuous speech

Jeanrenaud et al. (1993) introduced the notion of event spotting and showed that the detection of events could be approached as a word spotting problem. The present authors first concentrate on the problem of spotting complex units such as grammatic events and describe the three issues that have to be addressed. These issues are: 1) hypothesizing-how to detect an event, 2) scoring-how to generate a consistent score for the event, 3) identification-what word sequence constitutes the particular realization of the event. The authors also discuss ways to evaluate the performance of an event spotter and how to characterize the complexity of an event. They then present two approaches to spot events. The first approach is based on posterior probability scoring using sub-grammars, and the second uses a large vocabulary recognizer. They show that both approaches have comparable performance on an event spotting task using the Switchboard corpus. In the posterior probability scoring approach, however, there is the advantage of being able to choose an operating point.<<ETX>>