A review of physical and perceptual feature extraction techniques for speech, music and environmental sounds
Endowing machines with sensing capabilities similar to those of humans is a prevalent
quest in engineering and computer science. In the pursuit of making computers sense their …
quest in engineering and computer science. In the pursuit of making computers sense their …
Acoustic scene classification: a comprehensive survey
Acoustic scene classification (ASC) has gained significant interest recently due to its diverse
applications. Various audio signal processing and machine learning methods have been …
applications. Various audio signal processing and machine learning methods have been …
Optimizing acoustic feature extractor for anomalous sound detection based on Neyman-Pearson lemma
Y Koizumi, S Saito, H Uematsu… - 2017 25th European …, 2017 - ieeexplore.ieee.org
We propose a method for optimizing an acoustic feature extractor for anomalous sound
detection (ASD). Most ASD systems adopt outlier-detection techniques because it is difficult …
detection (ASD). Most ASD systems adopt outlier-detection techniques because it is difficult …
Anomalous sound detection using deep audio representation and a BLSTM network for audio surveillance of roads
Y Li, X Li, Y Zhang, M Liu, W Wang - Ieee Access, 2018 - ieeexplore.ieee.org
Surveillance systems based on image analysis can automatically detect road accidents to
ensure a quick intervention by rescue teams. However, in some situations, the visual …
ensure a quick intervention by rescue teams. However, in some situations, the visual …
Random forest classification based acoustic event detection utilizing contextual-information and bottleneck features
The variety of event categories and event boundary information have resulted in limited
success for acoustic event detection systems. To deal with this, we propose to utilize the …
success for acoustic event detection systems. To deal with this, we propose to utilize the …
Segmentation and characterization of acoustic event spectrograms using singular value decomposition
The traditional frame-based speech features such as Mel-frequency cepstral coefficients
(MFCCs) are specifically developed for speech/speaker recognition tasks. Speech is …
(MFCCs) are specifically developed for speech/speaker recognition tasks. Speech is …
Mel frequency cepstral coefficient temporal feature integration for classifying squeak and rattle noise
Fault identification using the emitted mechanical noise is becoming an attractive field of
research in a variety of industries. It is essential to rank acoustic feature integration functions …
research in a variety of industries. It is essential to rank acoustic feature integration functions …
A study of features and deep neural network architectures and hyper-parameters for domestic audio classification
Featured Application The algorithms explored in this research can be used for any multi-
level classification applications. Abstract Recent methodologies for audio classification …
level classification applications. Abstract Recent methodologies for audio classification …
SANet: A Compressed Speech Encoder and Steganography Algorithm Independent Steganalysis Deep Neural Network
S Li, J Wang, P Liu, K Shi - IEEE/ACM Transactions on Audio …, 2023 - ieeexplore.ieee.org
Most of the existing steganalysis methods for low-bit-rate compressed speech are
specifically designed for a particular speech encoder or category of steganography …
specifically designed for a particular speech encoder or category of steganography …
Pattern analysis based acoustic signal processing: a survey of the state-of-art
J Chaki - International Journal of Speech Technology, 2021 - Springer
Audio signal processing is the most challenging field in the current era for an analysis of an
audio signal. Audio signal classification (ASC) comprises of generating appropriate features …
audio signal. Audio signal classification (ASC) comprises of generating appropriate features …