Feature Extraction of Surround Sound Recordings for Acoustic Scene Classification

被引：3
|
作者：
Zielinski, Slawomir K. [1 ]
机构：
[1] Bialystok Tech Univ, Fac Comp Sci, Bialystok, Poland
来源：
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING (ICAISC 2018), PT II | 2018年 / 10842卷
关键词：
Machine listening; Acoustic scene classification; Feature extraction; Ensemble-based classifiers;
D O I：
10.1007/978-3-319-91262-2_43
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper extends the traditional methodology of acoustic scene classification based on machine listening towards a new class of multichannel audio signals. It identifies a set of new features of five-channel surround recordings for classification of the two basic spatial audio scenes. Moreover, it compares the three artificial intelligence-based classification approaches to audio scene classification. The results indicate that the method based on the early fusion of features is superior compared to those involving the late fusion of signal metrics.
引用
收藏
页码：475 / 486
页数：12
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