Papers Sound Classification
“Sound Classification” 태그가 달린 논문 148편 · 필터 해제
Environment Sound Classification using Multiple Feature Channels and Attention based Deep Convolutional Neural Network
In this paper, we propose a model for the Environment Sound Classification Task (ESC) that consists of multiple feature channels given as input to a Deep Convolutional Neural Network (CNN) with Attention mechanism. The n…
Data AugmentationEnvironment Sound ClassificationGeneral ClassificationSound ClassificationAI for Earth: Rainforest Conservation by Acoustic Surveillance
Saving rainforests is a key to halting adverse climate changes. In this paper, we introduce an innovative solution built on acoustic surveillance and machine learning technologies to help rainforest conservation. In part…
Audio ClassificationBIG-bench Machine LearningClassificationEnvironmental Sound Classification+2Sub-Spectrogram Segmentation for Environmental Sound Classification via Convolutional Recurrent Neural Network and Score Level Fusion
Environmental Sound Classification (ESC) is an important and challenging problem, and feature representation is a critical and even decisive factor in ESC. Feature representation ability directly affects the accuracy of …
ClassificationEnvironmental Sound ClassificationGeneral ClassificationSound ClassificationAttention based Convolutional Recurrent Neural Network for Environmental Sound Classification
Environmental sound classification (ESC) is a challenging problem due to the complexity of sounds. The ESC performance is heavily dependent on the effectiveness of representative features extracted from the environmental…
ClassificationEnvironmental Sound ClassificationGeneral ClassificationSound ClassificationContinual Learning of New Sound Classes using Generative Replay
Continual learning consists in incrementally training a model on a sequence of datasets and testing on the union of all datasets. In this paper, we examine continual learning for the problem of sound classification, in w…
AllContinual LearningSound ClassificationAn open access database for the evaluation of respiratory sound classification algorithms
###Objective: Over the last few decades, there has been significant interest in the automatic analysis of respiratory sounds. However, currently there are no publicly available large databases with which new algorithms c…
Sound ClassificationEnvironmental Sound Classification on Microcontrollers using Convolutional Neural Networks
Noise is a growing problem in urban areas, and according to the WHO is the second environmental cause of health problems in Europe. Noise monitoring using Wireless Sensor Networks are being applied in order to understand…
ClassificationCPUEnvironmental Sound ClassificationGeneral Classification+1Statistical feature embedding for heart sound classification
Cardiovascular Disease (CVD) is considered as one of the principal causes of death in the world. Over recent years, this field of study has attracted researchers' attention to investigate heart sounds' patterns for disea…
ClassificationDimensionality ReductionGeneral ClassificationSound ClassificationEnd-to-End Environmental Sound Classification using a 1D Convolutional Neural Network
In this paper, we present an end-to-end approach for environmental sound classification based on a 1D Convolution Neural Network (CNN) that learns a representation directly from the audio signal. Several convolutional la…
Environmental Sound ClassificationGeneral ClassificationSound ClassificationUnsupervised Feature Learning for Environmental Sound Classification Using Weighted Cycle-Consistent Generative Adversarial Network
In this paper we propose a novel environmental sound classification approach incorporating unsupervised feature learning from codebook via spherical $K$-Means++ algorithm and a new architecture for high-level data augmen…
BenchmarkingClassificationData AugmentationEnvironmental Sound Classification+3Snore-GANs: Improving Automatic Snore Sound Classification with Synthesized Data
One of the frontier issues that severely hamper the development of automatic snore sound classification (ASSC) associates to the lack of sufficient supervised training data. To cope with this problem, we propose a novel …
ClassificationData AugmentationDiversityGeneral Classification+1Sinusoidal wave generating network based on adversarial learning and its application: synthesizing frog sounds for data augmentation
Simulators that generate observations based on theoretical models can be important tools for development, prediction, and assessment of signal processing algorithms. In order to design these simulators, painstaking effor…
Data AugmentationSound ClassificationShort-segment heart sound classification using an ensemble of deep convolutional neural networks
This paper proposes a framework based on deep convolutional neural networks (CNNs) for automatic heart sound classification using short-segments of individual heart beats. We design a 1D-CNN that directly learns features…
General ClassificationSound ClassificationSpecificityAn Ensemble of Transfer, Semi-supervised and Supervised Learning Methods for Pathological Heart Sound Classification
In this work, we propose an ensemble of classifiers to distinguish between various degrees of abnormalities of the heart using Phonocardiogram (PCG) signals acquired using digital stethoscopes in a clinical setting, for …
General ClassificationRepresentation LearningSound ClassificationMasked Conditional Neural Networks for Environmental Sound Classification
The ConditionaL Neural Network (CLNN) exploits the nature of the temporal sequencing of the sound signal represented in a spectrogram, and its variant the Masked ConditionaL Neural Network (MCLNN) induces the network to …
ClassificationEnvironmental Sound ClassificationGeneral ClassificationSound ClassificationUtilizing Domain Knowledge in End-to-End Audio Processing
End-to-end neural network based approaches to audio modelling are generally outperformed by models trained on high-level data representations. In this paper we present preliminary work that shows the feasibility of train…
Environmental Sound ClassificationGeneral ClassificationSound ClassificationListening to the World Improves Speech Command Recognition
We study transfer learning in convolutional network architectures applied to the task of recognizing audio, such as environmental sound events and speech commands. Our key finding is that not only is it possible to trans…
Environmental Sound ClassificationGeneral ClassificationSound ClassificationTransfer LearningRecognizing Abnormal Heart Sounds Using Deep Learning
The work presented here applies deep learning to the task of automated cardiac auscultation, i.e. recognizing abnormalities in heart sounds. We describe an automated heart sound classification algorithm that combines the…
Deep LearningSensitivitySound ClassificationSpecificityComparison of Time-Frequency Representations for Environmental Sound Classification using Convolutional Neural Networks
Recent successful applications of convolutional neural networks (CNNs) to audio classification and speech recognition have motivated the search for better input representations for more efficient training. Visual display…
Audio ClassificationClassificationEnvironmental Sound ClassificationGeneral Classification+3Look, Listen and Learn
We consider the question: what can be learnt by looking at and listening to a large number of unlabelled videos? There is a valuable, but so far untapped, source of information contained in the video itself -- the corres…
Audio ClassificationGeneral ClassificationSound Classification