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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Detalles Bibliográficos
Autores principales: Lei, Y., Ferrer, L., McLaren, M., Scheffer, N., Chng E.S., Li H., Meng H., Ma B., Xie L., Amazon; Baidu; et al.; Google; Temasek Laboratories at Nanyang Technological University (TL at NTU); WeChat
Formato: CONF
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: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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