Skip to Main content Skip to Navigation
Conference papers

Combining transcription-based and acoustic-based speaker identifications for broadcast news

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.
Complete list of metadatas

Cited literature [12 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01433486
Contributor : Sylvain Meignier <>
Submitted on : Monday, April 3, 2017 - 9:57:26 PM
Last modification on : Thursday, February 7, 2019 - 5:55:46 PM
Document(s) archivé(s) le : Tuesday, July 4, 2017 - 2:50:28 PM

File

Khoury_ICASSP_2012.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Elie Khoury, Antoine Laurent, Sylvain Meignier, Simon Petitrenaud. Combining transcription-based and acoustic-based speaker identifications for broadcast news. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012), 2012, Kyoto, Japan. pp.4377 - 4380, ⟨10.1109/ICASSP.2012.6288889⟩. ⟨hal-01433486⟩

Share

Metrics

Record views

173

Files downloads

160