DocumentCode :
2958486
Title :
Sociometry based Multiparty Audio Recordings Segmentation
Author :
Vinciarelli, Alessandro
Author_Institution :
IDIAP Res. Inst., Martigny
fYear :
2006
fDate :
9-12 July 2006
Firstpage :
1801
Lastpage :
1804
Abstract :
This paper shows how social network analysis, the sociological domain studying the interaction between people in specific social environments, can be used to assign roles to different speakers in multiparty recordings. The experiments presented in this work focus on radio news recordings involving around 11 speakers on average. Each of them is assigned automatically a role (e.g. anchorman or guest) without using any information related to their identity or the amount of time they talk. The results (obtained over 96 recordings for a total of around 19 hours) show that more than 85% of the recording time is correctly labeled in terms of role
Keywords :
audio recording; speaker recognition; multiparty audio recording; radio news recording; social network analysis; sociometry; speaker segmentation; Audio recording; Automatic speech recognition; Data mining; Digital recording; Hidden Markov models; Humans; Information retrieval; Social network services; Statistics; Viterbi algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo, 2006 IEEE International Conference on
Conference_Location :
Toronto, Ont.
Print_ISBN :
1-4244-0366-7
Electronic_ISBN :
1-4244-0367-7
Type :
conf
DOI :
10.1109/ICME.2006.262902
Filename :
4036971
Link To Document :
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