Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research GroupsEIWOS

摘要

Most current speech recognition systems use hidden Markov models (HMMs) to deal with the temporal variability of speech and Gaussian mixture models (GMMs) to determine how well each state of each HMM fits a frame or a short window of frames of coefficients that represents the acoustic input. An alternative way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden lay...更多
个人信息

 

您的评分 :

IEEE Signal Process. Mag., pp. 82-97, 2012.

被引用次数4497|引用|60
标签
作者
评论