Title :
Combining transcription-based and acoustic-based speaker identifications for broadcast news
Author :
El Khoury, Elie ; Laurent, Antoine ; Meignier, Sylvain ; Petitrenaud, Simon
Author_Institution :
LIUM, Univ. du Maine-Le Mans, Le Mans, France
Abstract :
In this paper, we consider the issue of speaker identification within audio records of broadcast news. The speaker identity information is extracted from both transcript-based and acoustic-based speaker identification systems. This information is combined in the belief functions framework, which makes coherent the knowledge representation of the problem. The Kuhn-Munkres algorithm is used to optimize the assignment problem of speaker identities and speaker clusters. Experiments carried out on French broadcast news from the French evaluation campaign ESTER show the efficiency of the proposed combination method.
Keywords :
audio recording; belief networks; pattern clustering; speaker recognition; French broadcast news; French evaluation campaign ESTER; Kuhn-Munkres algorithm; acoustic-based speaker identifications; audio records; belief functions framework; knowledge representation; speaker clusters; speaker identities; speaker identity information; transcription-based speaker identifications; Acoustics; Computational modeling; Decoding; Error analysis; Hidden Markov models; Mathematical model; Training; Speaker identification; belief functions; speaker diarization;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-4673-0045-2
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2012.6288889
