CUED Publications database

Speaker diarisation and longitudinal linking in multi-genre broadcast data

Karanasou, P and Gales, MJF and Lanchantin, P and Liu, X and Qian, Y and Wang, L and Woodland, PC and Zhang, C (2016) Speaker diarisation and longitudinal linking in multi-genre broadcast data. In: UNSPECIFIED pp. 660-666..

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© 2015 IEEE. This paper presents a multi-stage speaker diarisation system with longitudinal Linking developed on BBC multi-genre data for the 2015 Multi-Genre Broadcast (MGB) challenge. The basic speaker diarisation system draws on techniques from the Cambridge March 2005 system with a new deep neural network (DNN)-based speech/non speech segmenter. A newly developed linking stage is next added to the basic diarisation output aiming at the identification of speakers across multiple episodes of the same series. The longitudinal constraint imposes an incremental processing of the episodes, where speaker labels for each episode can be obtained using only material from the episode in question, and those broadcast earlier in time. The nature of the data as well as the longitudinal linking constraint position this diarisation task as a new open-research topic, and a particularly challenging one. Different linking clustering metrics are compared and the lowest within-episode and cross-episode DER scores are achieved on the MGB challenge evaluation set.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Divisions: Div F > Machine Intelligence
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:01
Last Modified: 22 May 2018 06:59