Front-End Factor Analysis for Speaker Verification

Massachusetts Institute of Technology · Computer Research Institute of Montréal · +1 more institution

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Abstract

This paper presents an extension of our previous work which proposes a new speaker representation for speaker verification. In this modeling, a new low-dimensional speaker- and channel-dependent space is defined using a simple factor analysis. This space is named the total variability space because it models both speaker and channel variabilities. Two speaker verification systems are proposed which use this new representation. The first system is a support vector machine-based system that uses the cosine kernel to estimate the similarity between the input data. The second system directly uses the cosine similarity as the final decision score. We tested three channel compensation techniques in the total…

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5

Topics & keywords

Keywords
  • Normalization (sociology)
  • Computer science
  • Speaker recognition
  • Pattern recognition (psychology)
  • Speech recognition
  • Word error rate
  • Representation (politics)
  • NIST
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