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Title:
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Restricted Boltzmann Machine Supervectors for speaker recognition
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Author:
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Ghahabi, Omid; Hernando Pericás, Francisco Javier
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Other authors:
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Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla |
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Abstract:
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The use of Restricted Boltzmann Machines (RBM) is proposed in this paper as a non-linear transformation of GMM supervectors for speaker recognition. It will be shown that the RBM transformation will increase the discrimination power of raw GMM supervectors for speaker recognition. The experimental results on the core test condition of the NIST SRE 2006 corpus show that the proposed RBM supervectors will achieve a comparable performance to i-vectors. Furthermore, the combination of RBM supevectors and i-vectors in the score level improves the performance of the i-vector approach by more than 10% in terms of EER. |
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Abstract:
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Peer Reviewed |
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Subject(s):
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-Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la parla i del senyal acústic
-Automatic speech recognition
-Restricted Boltzmann Machine
-Speaker recognition
-Supervector
-Reconeixement automàtic de la parla |
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Rights:
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Document type:
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Article - Published version
Conference Object |
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Published by:
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Institute of Electrical and Electronics Engineers (IEEE)
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