J Dennis, HD Tran, ES Chng - IEEE Transactions on Audio …, 2012 - ieeexplore.ieee.org
The ability to automatically recognize a wide range of sound events in real-world conditions is an important part of applications such as acoustic surveillance and machine hearing. Our …
Classification of complex acoustic scenes under real time scenarios is an active domain which has engaged several researchers lately form the machine learning community. A …
S Song, C Zhang, Z Wei - IEEE Access, 2022 - ieeexplore.ieee.org
Urban sound event detection can automatically preload relevant information for a robot to ensure that it can be applied to various scene-activity tasks. To address the limitations of …
J Dennis, HD Tran, H Li - IEEE signal processing letters, 2010 - ieeexplore.ieee.org
In this letter, we present a novel feature extraction method for sound event classification, based on the visual signature extracted from the sound's time-frequency representation. The …
W Yang, S Krishnan - IEEE/ACM Transactions on Audio …, 2017 - ieeexplore.ieee.org
The popular frequency-domain features Mel-frequency cepstral coefficients (MFCCs) have been widely used for the task of acoustic scene classification (ASC). The MFCC feature …
This paper addresses the problem of sound event classification, focusing on feature extraction methods which are robust in noisy environments. In real world, sound events can …
Sound-event classification has emerged as an important field of research in recent years. In particular, investigations using sound data are being conducted in various industrial fields …
This work proposes the use of pseudo-color cochleagram image of sound signals for feature extraction for robust acoustic event recognition. A cochleagram is a variation of the …
This paper proposes an environmental sound segmentation method using Mask U-Net. In recent years, human–robot interactions, especially speech dialogue, have been assessed …