Name
Title | ||
|---|---|---|
A Neural-Network Approach for Speech Features Classification Based on Paraconsistent Logic |
Abstract | ||
|---|---|---|
In this paper, two independent Support Vector Machines were connected to a paraconsistent logic unit in order to establish a new classification scheme which takes into account the degrees of faith and uncertainty of a certain statement. By using this approach, one can classify an input signal as matching one of two independent classes or both of them. In our experiments, speech data constitute the classification elements which were adopted, and the results demonstrate the efficacy of the proposed approach. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ISM.2009.128 | ISM |
Keywords | Field | DocType |
neural-network approach,speech features classification,paraconsistent logic unit,new classification scheme,classification element,vector machines,paraconsistent logic,independent support,input signal,speech data,independent class,certain statement,neural network,classification,artificial neural networks,support vector machine,features,data mining,neural nets,speech processing,support vector machines,speech,svm,kernel | Kernel (linear algebra),Speech processing,Pattern recognition,Paraconsistent logic,Computer science,Classification scheme,Support vector machine,Artificial intelligence,Artificial neural network | Conference |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sylvio Barbon Júnior | 1 | 50 | 14.05 |
| Rodrigo Capobianco Guido | 2 | 161 | 27.59 |
| Lucimar Sasso Vieira | 3 | 20 | 4.85 |