Who Really Spoke When? Finding Speaker Turns and Identities in Broadcast News Audio

Automatic speaker segmentation and clustering methods have improved considerably over the last few years in the broadcast news domain. However, these generally still produce locally consistent relative labels (such as spkr1, spkr2) rather than true speaker identities (such as Bill Clinton, Ted Koppel). This paper presents a system which attempts to find these true identities from the text transcription of the audio using lexical pattern matching, and shows the effect on performance when using state-of-the-art speaker clustering and speech-to-text transcription systems instead of manual references