A Further Investigation on AR-Vector Models for Text Independent Speaker Identification
| dc.citation.bibtexName | inproceedings | en_US |
| dc.citation.conferenceName | IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) | en_US |
| dc.contributor.author | Magrin-Chagnolleau, Ivan | en_US |
| dc.contributor.author | Bimbot, Frederic | en_US |
| dc.contributor.org | Digital Signal Processing (http://dsp.rice.edu/) | en_US |
| dc.date.accessioned | 2007-10-31T00:52:12Z | |
| dc.date.available | 2007-10-31T00:52:12Z | |
| dc.date.issued | 1996-01-01 | en |
| dc.date.modified | 2004-11-05 | en_US |
| dc.date.note | 2004-01-14 | en_US |
| dc.date.submitted | 1996-01-01 | en_US |
| dc.description | Conference Paper | en_US |
| dc.description.abstract | In this paper, we investigate on the role of dynamic information on the performances of AR-vector models for speaker recognition. To this purpose, we design an experimental protocol that destroys the time structure of speech frame sequences, which we compare to a more conventional one, i.e. keeping the natural time order. These results are also compared with those obtained with a (single) Gaussian model. Several measures are systematically investigated in the three cases, and different ways of symmetrisation are tested. We observe that the destruction of the time order can be a factor of improvement for the AR-vector models, and that results obtained with the Gaussian model are merely always better. In most cases, symmetrisation is beneficial. | en_US |
| dc.identifier.citation | I. Magrin-Chagnolleau and F. Bimbot, "A Further Investigation on AR-Vector Models for Text Independent Speaker Identification," 1996. | |
| dc.identifier.doi | http://dx.doi.org/10.1109/ICASSP.1996.540300 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/20073 | |
| dc.language.iso | eng | |
| dc.subject | Temporary | * |
| dc.subject.keyword | Temporary | en_US |
| dc.subject.other | General DSP | en_US |
| dc.title | A Further Investigation on AR-Vector Models for Text Independent Speaker Identification | en_US |
| dc.type | Conference paper | |
| dc.type.dcmi | Text |