Diarization-based speaker retrieval for broadcast television archives

Abstract

In this study we extend a query-by-example diarizationbased speaker retrieval system to a full speaker retrieval system for broadcast television. The envisioned system is capable of finding all speakers in an archive using their names instead of example speech fragments. Information extracted from a television guide is used to label speaker clusters that most likely correspond to the found names. As part of the labeling process, all speaker clusters are first classified automatically based on their role in the programs they appear in. The role classification accuracy is 64% on our evaluation set. Speaker names can automatically be attributed to a fraction of the speaker clusters with an accuracy of 70%.

Constrained speaker linking

“…E.g., in [6], a sequence of meetings is processed with diarization, and later the speaker linking between meetings is carried out. Sometimes the speaker information is partially known, as in the case of the speaker diarization of broadcast shows where TV-guide metadata can reveal the names of some of the speakers in the shows [12].…”