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Graph Embedding for Pattern Analysis pp 229–260Cite as

Graph Embedding for Speaker Recognition

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Abstract

This chapter presents applications of graph embedding to the problem of text-independent speaker recognition. Speaker recognition is a general term encompassing multiple applications. At the core is the problem of speaker comparison—given two speech recordings (utterances), produce a score which measures speaker similarity. Using speaker comparison, other applications can be implemented—speaker clustering (grouping similar speakers in a corpus), speaker verification (verifying a claim of identity), speaker identification (identifying a speaker out of a list of potential candidates), and speaker retrieval (finding matches to a query set).

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Acknowledgements

This work was sponsored by the Department of Defense under Air Force Contract FA8721-05-C-0002. Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the United States Government.

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Authors and Affiliations

  1. University of Michigan, Ann Arbor, MI, USA

    Z. N. Karam

  2. MIT Lincoln Laboratory, Lexington, Massachusetts, 02420, USA

    W. M. Campbell

Authors
  1. Z. N. Karam
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  2. W. M. Campbell
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Correspondence to Z. N. Karam .

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Editors and Affiliations

  1. , Dept. of ECE, College of Engineering, Northeastern University, 403 Dana Research Center, 360 Huntington Ave, Boston, 02115, Massachusetts, USA

    Yun Fu

  2. Honeywell, Douglas Drive North 1985, Golden Valley, 55422, USA

    Yunqian Ma

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Karam, Z.N., Campbell, W.M. (2013). Graph Embedding for Speaker Recognition. In: Fu, Y., Ma, Y. (eds) Graph Embedding for Pattern Analysis. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4457-2_10

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  • DOI: https://doi.org/10.1007/978-1-4614-4457-2_10

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