scholarly journals Mel frequency cepstral coefficient temporal feature integration for classifying squeak and rattle noise

2021 ◽  
Vol 150 (1) ◽  
pp. 193-201
Author(s):  
Asith Abeysinghe ◽  
Mohammad Fard ◽  
Reza Jazar ◽  
Fabio Zambetta ◽  
John Davy
2021 ◽  
Vol 69 (4) ◽  
pp. 227-237
Author(s):  
Lazaros Vrysis ◽  
Leontios Hadjileontiadis ◽  
Iordanis Thoidis ◽  
Charalampos Dimoulas ◽  
George Papanikolaou

2007 ◽  
Vol 15 (5) ◽  
pp. 1654-1664 ◽  
Author(s):  
Anders Meng ◽  
Peter Ahrendt ◽  
Jan Larsen ◽  
Lars Kai Hansen

Author(s):  
Stavros Ntalampiras ◽  
Ilyas Potamitis ◽  
Nikos Fakotakis

2011 ◽  
Vol 49 (7) ◽  
pp. 1788-1793 ◽  
Author(s):  
Isabel Arend ◽  
Robert Rafal ◽  
Robert Ward

2020 ◽  
Vol 68 (1/2) ◽  
pp. 66-77 ◽  
Author(s):  
Lazaros Vrysis ◽  
Nikolaos Tsipas ◽  
Iordanis Thoidis ◽  
Charalampos Dimoulas

Acoustics ◽  
2019 ◽  
Vol 1 (2) ◽  
pp. 410-422 ◽  
Author(s):  
Vasileios Bountourakis ◽  
Lazaros Vrysis ◽  
Konstantinos Konstantoudakis ◽  
Nikolaos Vryzas

Temporal feature integration refers to a set of strategies attempting to capture the information conveyed in the temporal evolution of the signal. It has been extensively applied in the context of semantic audio showing performance improvements against the standard frame-based audio classification methods. This paper investigates the potential of an enhanced temporal feature integration method to classify environmental sounds. The proposed method utilizes newly introduced integration functions that capture the texture window shape in combination with standard functions like mean and standard deviation in a classification scheme of 10 environmental sound classes. The results obtained from three classification algorithms exhibit an increase in recognition accuracy against a standard temporal integration with simple statistics, which reveals the discriminative ability of the new metrics.


2006 ◽  
Vol 2 (1) ◽  
pp. 77-85 ◽  
Author(s):  
Michael H. Herzog ◽  
Elisabeth Lesemann ◽  
Christian W. Eurich

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