Name
Abstract | ||
|---|---|---|
This paper focuses on speaker detection using multispeaker files both for the enrollment phase and for the test phase. This task was introduced during the 2002 NIST speaker recognition evaluation campaign. Enrollment data is composed of three two-speaker files. Test files are also two-speaker records. The system presented here uses a speaker segmentation process based on an HMM conversation model followed by a speaker matching technique to produce one-speaker segments. Speaker detection is then achieved using AMIRAL, LIA's GMM-based speaker verification system. Validation of the proposed strategy is done using extracts from the NIST 2002 results. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/ICASSP.2003.1202298 | ICASSP '03). 2003 IEEE International Conference |
Keywords | Field | DocType |
hidden Markov models,speaker recognition,2002 NIST speaker recognition evaluation,AMIRAL,HMM conversation model,LIA GMM-based speaker verification system,enrollment data,multispeaker audio files,one-speaker segments,speaker detection,speaker matching technique,speaker segmentation,test data,two-speaker files,two-speaker records | Computer science,Speaker recognition,Speaker diarisation,Natural language processing,Artificial intelligence,Loudspeaker,Viterbi algorithm,Pattern recognition,Segmentation,Speech recognition,NIST,Test data,Hidden Markov model | Conference |
Volume | ISSN | ISBN |
2 | 1520-6149 | 0-7803-7663-3 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jean-François Bonastre | 1 | 64 | 10.60 |
| Sylvain Meignier | 2 | 0 | 0.34 |
| Téva Merlin | 3 | 0 | 0.34 |