Name
Title | ||
|---|---|---|
Selection of features and combination of classifiers using a fuzzy approach for acoustic event classification |
Abstract | ||
|---|---|---|
In this paper, we aim to improve the classification of human non-speech sounds produced in a meeting-room environment by using concepts and tools from the fuzzy theory. Starting with an SVM-based baseline system, firstly a reduction of the number of features with the fuzzy measure is shown. And, secondly, a noticeable improvement of the classification performance is reported by combining the outputs of two classification systems with the fuzzy integral. |
Year | Venue | Keywords |
|---|---|---|
2005 | INTERSPEECH | classification system |
Field | DocType | Citations |
Neuro-fuzzy,Pattern recognition,Fuzzy classification,Defuzzification,Computer science,Fuzzy set operations,Support vector machine,Fuzzy logic,Artificial intelligence,Adaptive neuro fuzzy inference system,Baseline system,Machine learning | Conference | 1 |
PageRank | References | Authors |
0.39 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrey Temko | 1 | 271 | 22.04 |
| Dusan Macho | 2 | 47 | 6.58 |
| Climent Nadeu | 3 | 611 | 60.16 |