(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2016-12) Siriwardene, S; Fernando, KSD
Acoustic modeling refers to a statistical model that converts the speech signal to a set of phonetics related
to each set of feature vectors extracted through pre processing the sound signal. A traditional approach to this
problem is Hidden Markov Models (HMM), a probability model that maps each input with a hidden state. Deep
neural networks are used for acoustic modeling due to their efficient feature extraction ability. This paper reviews
the various forms of neural networks used in combination with HMMs for speech recognition.
