A deep neural network speaker verification system targeting microphone speech

We recently proposed the use of deep neural networks (DNN) in place of Gaussian Mixture models (GMM) in the i-vector extraction process for speaker recognition. We have shown significant accuracy improvements on the 2012 NIST speaker recognition evaluation (SRE) telephone conditions. This paper expl...

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Guardado en:
Detalles Bibliográficos
Publicado: 2014
Materias:
Deep neural networks
I-vectors
Microphone data
Speaker recognition
Microphones
Speech
Speech communication
Telephone sets
Accuracy Improvement
Gaussian Mixture Model
In-depth analysis
Speaker recognition evaluations
Speaker verification system
Speech recognition
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_2308457X_v_n_p681_Lei
http://hdl.handle.net/20.500.12110/paper_2308457X_v_n_p681_Lei
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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