Machine Learning Algorithms for Environmental Sound Recognition: Towards Soundscape Semantics

被引：28

作者：

Bountourakis, Vasileios ^{[1
]}

Vrysis, Lazaros ^{[1
]}

Papanikolaou, George ^{[1
]}

机构：

[1] Aristotle Univ Thessaloniki, AUTh Univ Campus, Thessaloniki 54124, Greece

来源：

PROCEEDINGS OF THE 10TH AUDIO MOSTLY: A CONFERENCE ON INTERACTION WITH SOUND, AM'15 | 2015年

关键词：

Environmental Sound Recognition; audio classification; semantic audio analysis; computer audition; feature extraction; feature selection; machine learning algorithms;

D O I：

10.1145/2814895.2814905

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This paper investigates methods aiming at the automatic recognition and classification of discrete environmental sounds, for the purpose of subsequently applying these methods to the recognition of soundscapes. Research in audio recognition has traditionally focused on the domains of speech and music. Comparatively little research has been done towards recognizing non-speech environmental sounds. For this reason, in this paper, we apply existing techniques that have been proved efficient in the other two domains. These techniques are comprehensively compared to determine the most appropriate one for addressing the problem of environmental sound recognition.

引用

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