Parallelizing Speaker-Attributed Speech Recognition for Meeting Browsing

The following article presents an application for browsing meeting recordings by speaker and keyword which we call the Meeting Diarist. The goal of the system is to enable browsing of the content with rich meta-data in a graphical user interface shortly after the end of meeting, even when the application runs on a contemporary laptop. We there-fore developed novel parallel methods for speaker diarization and multi-hypothesis speech recognition that are optimized to run on multicore and many core architectures. This paper presents the underlying parallel speaker diarization and speech recognition realizations, a comparison of results based on NIST RT07 evaluation data, and a description of the final application.