Name
Title | ||
|---|---|---|
Hybrid Deep Neural Network--Hidden Markov Model (DNN-HMM) Based Speech Emotion Recognition |
Abstract | ||
|---|---|---|
Deep Neural Network Hidden Markov Models, or DNN-HMMs, are recently very promising acoustic models achieving good speech recognition results over Gaussian mixture model based HMMs (GMM-HMMs). In this paper, for emotion recognition from speech, we investigate DNN-HMMs with restricted Boltzmann Machine (RBM) based unsupervised pre-training, and DNN-HMMs with discriminative pre-training. Emotion recognition experiments are carried out on these two models on the eNTERFACE'05 database and Berlin database, respectively, and results are compared with those from the GMM-HMMs, the shallow-NN-HMMs with two layers, as well as the Multi-layer Perceptrons HMMs (MLP-HMMs). Experimental results show that when the numbers of the hidden layers as well hidden units are properly set, the DNN could extend the labeling ability of GMM-HMM. Among all the models, the DNN-HMMs with discriminative pre-training obtain the best results. For example, for the eNTERFACE'05 database, the recognition accuracy improves 12.22% from the DNN-HMMs with unsupervised pre-training, 11.67% from the GMM-HMMs, 10.56% from the MLP-HMMs, and even 17.22% from the shallow-NN-HMMs, respectively. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ACII.2013.58 | ACII |
Keywords | Field | DocType |
recognition accuracy,good speech recognition result,multilayer perceptrons hmm,boltzmann machines,speech recognition,berlin database,hidden layer,multi-layer perceptrons hmms,hybrid deep neural network-hidden markov model based speech emotion recognition,acoustic models,emotion recognition experiment,discriminative pre-training,hidden unit,emotion recognition,hidden markov model,rbm,gmm-hmm,speech emotion recognition,gaussian mixture model based hmm,unsupervised pre-training,dnn-hmm,hybrid deep neural network,hidden markov models,restricted boltzmann machine,unsupervised learning,enterface 05 database | Restricted Boltzmann machine,Pattern recognition,Emotion recognition,Computer science,Speech recognition,Unsupervised learning,Artificial intelligence,Artificial neural network,Hidden Markov model,Discriminative model,Perceptron,Mixture model | Conference |
ISSN | Citations | PageRank |
2156-8103 | 25 | 0.98 |
References | Authors | |
9 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Longfei Li | 1 | 35 | 1.47 |
| Yong Zhao | 2 | 32 | 4.11 |
| Jiang Dongmei | 3 | 115 | 15.28 |
| Yanning Zhang | 4 | 1613 | 176.32 |
| Fengna Wang | 5 | 41 | 2.94 |
| Isabel Gonzalez | 6 | 54 | 5.10 |
| V. Enescu | 7 | 105 | 10.66 |
| Hichem Sahli | 8 | 475 | 65.19 |