Abstract
This paper summarizes the LIMSI participation in the CLEAR'06 acoustic speaker identification task that aims to identify speakers in CHIL seminars via the acoustic channel. The system consists of a standard Gaussian mixture model based system similar to systems developed for the NIST speaker recognition evaluations and includies feature warping of cepstral coefficients and MAP adaptation of a Universal Background Model. Several computational optimizations were implemented for real-time efficiency: stochastic frame subsampling for training, top-Gaussians scoring and auto-adaptive pruning for the tests, speeding up the system by more than a factor of ten. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Barras, C., Zhu, X., Gauvain, J. L., & Lamel, L. (2007). The CLEAR’06 LIMSI acoustic speaker identification system for CHIL seminars. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4122 LNCS, pp. 233–240). Springer Verlag. https://doi.org/10.1007/978-3-540-69568-4_20
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