Add to ORKGThis paper presents environmental sound classification system and performance comparison on ESC 10 dataset. The feature extraction method includes cochlea and auditory nerve models. Classification model includes classic convolutional neuron network architectures. Experiments based on different architectures of convolutional neural networks and proposed feature extraction method. The model outperforms baseline implementations and achieves results comparable to other state-of-the-art approaches
Abstract Environmental sound classification is one of the important issues in the audio recognition ...
The topic of this thesis work is soft computing based feature selection for environmental sound clas...
Context. Environmental Sound Recognition, unlike Speech Recognition, is an area that is still in the...
At present, the environment sound recognition system mainly identifies environment sounds with deep ...
A convolutional neural network (CNN) training framework is described and implemented. The framework ...
The classification of environmental sounds is important for emerging applications such as automatic ...
With deep great breakthroughs of deep learning in the field of computer vision, the field of audio r...
Research in sound classification and recognition is rapidly advancing in the field of pattern recogn...
Research in sound classification and recognition is rapidly advancing in the field of pattern recogn...
In the important and challenging field of environmental sound classification (ESC), a crucial and ev...
Artificial neural networks are computational systems made up of simple processing units that have a ...
Artificial neural networks have in the last decade been a vital tool in image recognition, signal pr...
International audienceIn this paper we describe algorithms to classify environmental sounds with the...
Environmental Sound Classification (ESC) plays a vital role in machine auditory scene perception. De...
Classification of environmental sounds plays a key role in security, investigation, robotics since t...
Abstract Environmental sound classification is one of the important issues in the audio recognition ...
The topic of this thesis work is soft computing based feature selection for environmental sound clas...
Context. Environmental Sound Recognition, unlike Speech Recognition, is an area that is still in the...
At present, the environment sound recognition system mainly identifies environment sounds with deep ...
A convolutional neural network (CNN) training framework is described and implemented. The framework ...
The classification of environmental sounds is important for emerging applications such as automatic ...
With deep great breakthroughs of deep learning in the field of computer vision, the field of audio r...
Research in sound classification and recognition is rapidly advancing in the field of pattern recogn...
Research in sound classification and recognition is rapidly advancing in the field of pattern recogn...
In the important and challenging field of environmental sound classification (ESC), a crucial and ev...
Artificial neural networks are computational systems made up of simple processing units that have a ...
Artificial neural networks have in the last decade been a vital tool in image recognition, signal pr...
International audienceIn this paper we describe algorithms to classify environmental sounds with the...
Environmental Sound Classification (ESC) plays a vital role in machine auditory scene perception. De...
Classification of environmental sounds plays a key role in security, investigation, robotics since t...
Abstract Environmental sound classification is one of the important issues in the audio recognition ...
The topic of this thesis work is soft computing based feature selection for environmental sound clas...
Context. Environmental Sound Recognition, unlike Speech Recognition, is an area that is still in the...