Name
Abstract | ||
|---|---|---|
The EGCs can calculate a human being's current emotion from the content of the utterance. In this paper, we extend the EGCs to refer variance of emotions based on Hidden Markov Model (HMM). Because the EGCs focus on 20 types of emotion, a 20-dimension vector is checked for a stimulus from external world. The enfeeblement process of the emotion vector's degree is expressed by the exponential distribution function and the current emotion vector is calculated based on HMM. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/978-3-540-45226-3_58 | LECTURE NOTES IN COMPUTER SCIENCE |
Keywords | Field | DocType |
exponential distribution,hidden markov model | Pattern recognition,Computer science,Utterance,Speech recognition,Exponential distribution,Artificial intelligence,Hidden Markov model,Hidden semi-Markov model | Conference |
Volume | ISSN | Citations |
2774 | 0302-9743 | 1 |
PageRank | References | Authors |
0.37 | 1 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kazuya Mera | 1 | 10 | 6.46 |
| Takumi Ichimura | 2 | 120 | 35.31 |