DocumentCode
596787
Title
The hybrid model of affective recognition based on HMM and PNN
Author
Jianing Tong ; Yahan Zhang
Author_Institution
ShiJiaZhuang Vocational Technol. Inst., Shijiazhuang, China
fYear
2012
fDate
18-20 Oct. 2012
Firstpage
1216
Lastpage
1218
Abstract
Speech affective recognition is an important branch of speech recognition, whose main purpose is the emotional characteristics included in the analysis of speech signals. Because the use of a single model to identify which identify significant limitations. This paper presents a recognition model based on HMM and PNN, which using PNN for classification and using HMM for generating feature matching sequence. The experimental results show that high recognition rate in a single the HMM.
Keywords
emotion recognition; feature extraction; hidden Markov models; neural nets; probability; signal classification; speech recognition; HMM; PNN; classification; emotional characteristics; feature matching sequence; hybrid model; identify significant limitations; recognition model; speech affective recognition; speech recognition; speech signals; Hidden Markov models; Neural networks; Neurons; Probabilistic logic; Speech recognition; Support vector machine classification; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4673-1743-6
Type
conf
DOI
10.1109/ICACI.2012.6463370
Filename
6463370
Link To Document