Encyclopedia of Biometrics

2009 Edition
| Editors: Stan Z. Li, Anil Jain

Speaker Segmentation

Reference work entry
DOI: https://doi.org/10.1007/978-0-387-73003-5_202
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Synonyms

Definition

Speaker segmentation is the process of partitioning an input audio stream into acoustically homogeneous segments according to the speaker identity. A typical speaker segmentation system finds potential speaker change points using the audio characteristics.

Introduction

Segmenting an audio–visual stream by its constituent speakers is essential in many application domains. First, for audio–visual documents, speaker changes are often considered natural points around which to structure the document for navigation by listeners (speaker indexing). In broadcast news, for example, speaker changes typically coincide with story changes or transitions. Audio recordings of meetings, presentations, and panel discussions are also examples where organizing audio segments by speaker identity can provide useful navigational cues to listeners. Furthermore, an accurate speaker segmentation system is also necessary for...

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References

  1. 1.
    Docio-Fernandez, L., Garcia-Mateo, C.: Speaker segmentation, detection and tracking in multi-speaker long audio recordings. In: Third COST 275 Workshop: Biometrics on the Internet, pp. 97–100. Hatfield, UK (2005)Google Scholar
  2. 2.
    Chen, S.S., Gopalakrishnan, P.: Clustering via the bayesian information criterion with applications in speech recognition. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 2, pp. 645–648. Seattle, WA (1998)Google Scholar
  3. 3.
    Delacourt, P., Wellekens, C.J.: DISTBIC: a speaker-based segmentation for audio data indexing. Speech Commun. 32(1–2), 111–126 (2000)CrossRefGoogle Scholar
  4. 4.
    Lu, L., Zhang, H.J.: Speaker change detection and tracking in real-time news broadcasting analysis. In: ACM International Conference on Multimedia, pp. 602–610. Quebec, QC, Canada (2002)Google Scholar
  5. 5.
    Campbell, J.P.: Speaker recognition: a tutorial. Proc. IEEE 85(9), 1437–1462 (1997)CrossRefGoogle Scholar
  6. 6.
    Gauvain, J.L., Lamel, L., Adda, G.: Partitioning and transcription of broadcast news data. In: Proceedings of International Conference on Speech and Language Processing, vol. 4, pp. 1335–1338. Sidney, Australia (1998)Google Scholar
  7. 7.
    Kemp, T., Schmidt, M., Westphal, M., Waibel, A.: Strategies for automatic segmentation of audio data. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 1423–1426. Istanbul, Turkey (2000)Google Scholar
  8. 8.
    Gauvain, J.L., Lamel, L., Adda, G.: The LIMSI broadcast news transcription system. Speech Commun. 37(1–2), 89–108 (2002)zbMATHCrossRefGoogle Scholar
  9. 9.
    Moraru, D., Meignier, S., Fredouille, C., Besacier, L., Bonastre, J.F.: The ELISA consortium approaches in broadcast news speaker segmentation during the NIST 2003 rich transcription evaluation. In: Proceedings of IEEE ICASSP’04, pp. 223–228. Montreal, Canada (2004)Google Scholar
  10. 10.
    Lu, L., Li, S.Z., Zhang, H.J.: Content-based audio segmentation using support vector machines. ACM Multimedia Syst. J. 8(6), 482–492 (2001)CrossRefGoogle Scholar
  11. 11.
    Kim, H.G., Ertelt, D., Sikora, T.: Hybrid speaker-based segmentation system using model-level clustering. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 1, pp. 745–748. Philadelphia, PA (2005)Google Scholar
  12. 12.
    Vescovi, M., Cettolo, M., Rizzi, R.: A DP algoritm for speaker change detection. In: Proceedings of Eurospeech03. (2003)Google Scholar
  13. 13.
    Pwint, M., Sattar, F.: A segmentation method for noisy speech using genetic algorithm. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing. Philadelphia, PA (2005)Google Scholar
  14. 14.
    Lathoud, G., McCowan, I., Odobez, J.: Unsupervised location-based segmentation of multi-party speech. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing: NIST Meeting Recognition Workshop. Montreal, Canada (2004)Google Scholar
  15. 15.
    Perez-Freire, L., Garcia-Mateo, C.: A multimedia approach for audio segmentation in TV broadcast news. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 369–372. Montreal, QC, Canada (2004)Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.E.T.S. de Ingenieros deTelecomunicaciónUniversity of VigoVigoSpain
  2. 2.Department of Signal Theory and CommunicationsUniversity of VigoVigoSpain