Locally Recurrent Probabilistic Neural Networks with Application to Speaker Verification
暂无分享,去创建一个
Todor Ganchev | Dimitris K. Tasoulis | Michael N. Vrahatis | Nikos Fakotakis | M. N. Vrahatis | N. Fakotakis | T. Ganchev | D. Tasoulis
[1] Joseph Bibb Cain. Improved probabilistic neural network and its performance relative to other models , 1990, Defense, Security, and Sensing.
[2] Dominique Genoud,et al. POLYCOST: A telephone-speech database for speaker recognition , 2000, Speech Commun..
[3] Jirí Benes,et al. On neural networks , 1990, Kybernetika.
[4] Michael R. Berthold,et al. Constructive training of probabilistic neural networks , 1998, Neurocomputing.
[5] Robert B. Ash,et al. Information Theory , 2020, The SAGE International Encyclopedia of Mass Media and Society.
[6] Ah Chung Tsoi,et al. FIR and IIR Synapses, a New Neural Network Architecture for Time Series Modeling , 1991, Neural Computation.
[7] Nicos G. Pavlidis,et al. Optimizing the Performance of Probabilistic Neural Networks in a BioinformaticsTa sk , 2004 .
[8] Donald F. Specht,et al. Probabilistic neural networks , 1990, Neural Networks.
[9] B. Atal. Effectiveness of linear prediction characteristics of the speech wave for automatic speaker identification and verification. , 1974, The Journal of the Acoustical Society of America.
[10] L. Baum,et al. Statistical Inference for Probabilistic Functions of Finite State Markov Chains , 1966 .
[11] Dimitris K. Tasoulis,et al. Locally recurrent probabilistic neural network for text-independent speaker verification , 2003, INTERSPEECH.
[12] Todor Ganchev,et al. TEXT-INDEPENDENT SPEAKER VERIFICATION BASED ON PROBABILISTIC NEURAL NETWORKS , 2002 .
[13] Mahmood R. Azimi-Sadjadi,et al. Temporal updating scheme for probabilistic neural network with application to satellite cloud classification , 2000, IEEE Trans. Neural Networks Learn. Syst..
[14] Geoffrey E. Hinton,et al. Phoneme recognition using time-delay neural networks , 1989, IEEE Trans. Acoust. Speech Signal Process..
[15] Sheng Chen,et al. Robust maximum likelihood training of heteroscedastic probabilistic neural networks , 1998, Neural Networks.
[16] Timothy Masters,et al. Practical neural network recipes in C , 1993 .
[17] Sun-Yuan Kung,et al. Estimation of elliptical basis function parameters by the EM algorithm with application to speaker verification , 2000, IEEE Trans. Neural Networks Learn. Syst..
[18] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[19] R. Storn,et al. Differential Evolution - A simple and efficient adaptive scheme for global optimization over continuous spaces , 2004 .
[20] Peter E. Hart,et al. Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.
[21] H Hermansky,et al. Perceptual linear predictive (PLP) analysis of speech. , 1990, The Journal of the Acoustical Society of America.
[22] R. Redner,et al. Mixture densities, maximum likelihood, and the EM algorithm , 1984 .
[23] D. F. Specht,et al. Enhancements to probabilistic neural networks , 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.
[24] William S. Meisel,et al. Computer-oriented approaches to pattern recognition , 1972 .
[25] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .