DocumentCode :
2984565
Title :
A visualized acoustic saliency feature extraction method for environment sound signal processing
Author :
Jingyu Wang ; Ke Zhang ; Madani, Kurash ; Sabourin, Christophe
Author_Institution :
Sch. of Astronaut., Northwestern Polytech. Univ., Xi´an, China
fYear :
2013
fDate :
22-25 Oct. 2013
Firstpage :
1
Lastpage :
4
Abstract :
Environment perception is an important research issue for both unmanned ground vehicles and robots. To improve the capacity of perception, a visualized acoustic saliency feature extraction (VASFE) method based on both the short-time Fourier transform (STFT) and the Mel-Frequency Cepstrum Coefficient (MFCC) for environment sound signal processing is proposed in this paper. Sound signal is visualized by using the STFT algorithm as local image feature and the Mel-Frequency Cepstrum Coefficient (MFCC) is used to represent the local acoustic feature of the signal. The proposed VASFE method is tested by the natural sound data which collected from real world of both indoor and outdoor environment. The results show that this method is able to extract the saliency features of both long-term and short-term sound signal successfully and clearly, and conducts to very distinguishable features for future processing of environment sound information.
Keywords :
Fourier transforms; acoustic signal processing; cepstral analysis; data visualisation; feature extraction; MFCC; STFT algorithm; VASFE method; environment perception; environment sound information; environment sound signal processing; indoor environment; local acoustic feature; local image feature; long-term sound signal; mel-frequency cepstrum coefficient; natural sound data; outdoor environment; perception capacity; robots; short-term sound signal; short-time Fourier transform; sound signal visualization; unmanned ground vehicles; visualized acoustic saliency feature extraction method; Equations; Feature extraction; Mel frequency cepstral coefficient; Signal processing algorithms; Spectrogram; Visualization; MFCC; STFT algorithm; environment perception; natural sound; spectrogram; visualized acoustic saliency;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON 2013 - 2013 IEEE Region 10 Conference (31194)
Conference_Location :
Xi´an
ISSN :
2159-3442
Print_ISBN :
978-1-4799-2825-5
Type :
conf
DOI :
10.1109/TENCON.2013.6718918
Filename :
6718918
Link To Document :
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