In this paper we investigate the effect of Gaussian stochastic neurons on DNN acoustic modeling. The pre-Gaussian stochastic term can be viewed as a variant of ...

We investigate the effectiveness of Gaussian stochastic neurons in terms of model regularization and training acceleration. In our exper- iments, Gaussian ...

In this paper we investigate the effect of Gaussian stochastic neurons on DNN acoustic modeling. The pre-Gaussian stochastic term can be viewed as a variant of ...

Regularizing DNN Acoustic Models with Gaussian Stochastic Neurons. The 40th IEEE International Conference on Acoustics, Speech, and Signal Processing ...

In this paper we investigate the effect of Gaussian stochastic neurons on DNN acoustic modeling. The pre-Gaussian stochastic term can be viewed as a variant of ...

"regularizing dnn acoustic models with gaussian stochastic neurons"^^<http://www.w3.org/2001/XMLSchema#string>. 5. <http://aida.kmi.open.ac.uk/resource ...

ABSTRACT. This paper presents a deep recurrent regularization neural network (DRRNN) for speech recognition. Our idea is to build a regularization neural ...

May 22, 2018 · Title of thesis : Speaker adaptation of deep neural network acoustic models using Gaussian mixture model framework in automatic speech ...

May 21, 2015 · Acoustic models based on a Hidden Markov Model (HMM) and DNN hybrid result in 10-30% relative improvement in word error rates over traditional ...

Conventional deep neural networks (DNN) for speech acoustic mod- eling rely on Gaussian mixture models (GMM) and hidden Markov model (HMM) to obtain binary ...