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