Discriminative In-Set/Out-of-Set Speaker Recognition

@article{Angkititrakul2007DiscriminativeIS,
  title={Discriminative In-Set/Out-of-Set Speaker Recognition},
  author={Pongtep Angkititrakul and John H. L. Hansen},
  journal={IEEE Transactions on Audio, Speech, and Language Processing},
  year={2007},
  volume={15},
  pages={498-508}
}
In this paper, the problem of identifying in-set versus out-of-set speakers for limited training/test data durations is addressed. The recognition objective is to form a decision regarding an input speaker as being a legitimate member of a set of enrolled speakers or outside speakers. The general goal is to perform rapid speaker model construction from limited enrollment and test size resources for in-set testing for input audio streams. In-set detection can help ensure security and proper… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 31 REFERENCES

Speaker recognition with polynomial classifiers

  • IEEE Trans. Speech and Audio Processing
  • 2002
VIEW 13 EXCERPTS
HIGHLY INFLUENTIAL

A study on the effect of adding new dimensions to trajectories in the acoustic space

D. Albesano, R. De Mori, R. Gmello, F. Mana
  • Proc. EUROSPEECH/INTERSPEECH, 1999, pp. 4:1503–4:1506.
  • 1999
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Experimental evaluation of features for robust speaker identification

D. A. Reynolds
  • IEEE Trans. Speech Audio Process., vol. 2, no. 4, pp. 639–643, Oct. 1994.
  • 1994
VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL

Identifying in-set and out-of-set speakers using neighborhood information

  • 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing
  • 2004
VIEW 2 EXCERPTS

Minimum verification error training for topic verification

  • 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).
  • 2003
VIEW 2 EXCERPTS

Open set text-independent speaker recognition based on set-score pattern classification

  • 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).
  • 2003
VIEW 1 EXCERPT