Papers Environmental Sound Classification
“Environmental Sound Classification” 태그가 달린 논문 50편 · 필터 해제
AUCO ResNet: an end-to-end network for Covid-19 pre-screening from cough and breath
This study presents the Auditory Cortex ResNet (AUCO ResNet), it is a biologically inspired deep neural network especially designed for sound classification and more specifically for Covid-19 recognition from audio track…
8kAudio ClassificationCOVID-19 DiagnosisData Augmentation+4Responding to Challenge Call of Machine Learning Model Development in Diagnosing Respiratory Disease Sounds
In this study, a machine learning model was developed for automatically detecting respiratory system sounds such as sneezing and coughing in disease diagnosis. The automatic model and approach development of breath sound…
BIG-bench Machine LearningClassificationEnvironmental Sound ClassificationSound ClassificationA Preliminary Study on Environmental Sound Classification Leveraging Large-Scale Pretrained Model and Semi-Supervised Learning
With the widespread commercialization of smart devices, research on environmental sound classification has gained more and more attention in recent years. In this paper, we set out to make effective use of large-scale au…
ClassificationData AugmentationEnvironmental Sound ClassificationSound Classification+1AudioCLIP: Extending CLIP to Image, Text and Audio
In the past, the rapidly evolving field of sound classification greatly benefited from the application of methods from other domains. Today, we observe the trend to fuse domain-specific tasks and approaches together, whi…
ClassificationEnvironmental Sound ClassificationSound ClassificationZero-Shot Environment Sound ClassificationEnvGAN: Adversarial Synthesis of Environmental Sounds for Data Augmentation
The research in Environmental Sound Classification (ESC) has been progressively growing with the emergence of deep learning algorithms. However, data scarcity poses a major hurdle for any huge advance in this domain. Dat…
Data AugmentationEnvironmental Sound ClassificationSound ClassificationTiny Transformers for Environmental Sound Classification at the Edge
With the growth of the Internet of Things and the rise of Big Data, data processing and machine learning applications are being moved to cheap and low size, weight, and power (SWaP) devices at the edge, often in the form…
ClassificationEnvironmental Sound ClassificationGeneral ClassificationSound ClassificationEnvironmental Sound Classification on the Edge: A Pipeline for Deep Acoustic Networks on Extremely Resource-Constrained Devices
Significant efforts are being invested to bring state-of-the-art classification and recognition to edge devices with extreme resource constraints (memory, speed, and lack of GPU support). Here, we demonstrate the first d…
Audio ClassificationEnvironmental Sound ClassificationGPUModel Compression+2SoundCLR: Contrastive Learning of Representations For Improved Environmental Sound Classification
Environmental Sound Classification (ESC) is a challenging field of research in non-speech audio processing. Most of current research in ESC focuses on designing deep models with special architectures tailored for specifi…
Contrastive LearningData AugmentationEnvironmental Sound ClassificationEnvironment Sound Classification+3Comparison of semi-supervised deep learning algorithms for audio classification
In this article, we adapted five recent SSL methods to the task of audio classification. The first two methods, namely Deep Co-Training (DCT) and Mean Teacher (MT), involve two collaborative neural networks. The three ot…
Audio ClassificationAudio TaggingData AugmentationDeep Learning+3Urban Sound Classification : striving towards a fair comparison
Urban sound classification has been achieving remarkable progress and is still an active research area in audio pattern recognition. In particular, it allows to monitor the noise pollution, which becomes a growing concer…
Audio ClassificationAudio TaggingClassificationEnvironmental Sound Classification+2CRNNs for Urban Sound Tagging with spatiotemporal context
This paper describes CRNNs we used to participate in Task 5 of the DCASE 2020 challenge. This task focuses on hierarchical multilabel urban sound tagging with spatiotemporal context. The code is available on our GitHub r…
Audio ClassificationAudio TaggingEnvironmental Sound ClassificationRethinking CNN Models for Audio Classification
In this paper, we show that ImageNet-Pretrained standard deep CNN models can be used as strong baseline networks for audio classification. Even though there is a significant difference between audio Spectrogram and stand…
Audio ClassificationClassificationEnvironmental Sound ClassificationGeneral Classification+2An Ensemble of Convolutional Neural Networks for Audio Classification
In this paper, ensembles of classifiers that exploit several data augmentation techniques and four signal representations for training Convolutional Neural Networks (CNNs) for audio classification are presented and teste…
Audio ClassificationClassificationData AugmentationEnvironmental Sound Classification+2ESResNet: Environmental Sound Classification Based on Visual Domain Models
Environmental Sound Classification (ESC) is an active research area in the audio domain and has seen a lot of progress in the past years. However, many of the existing approaches achieve high accuracy by relying on domai…
ClassificationEnvironmental Sound ClassificationGeneral ClassificationSound ClassificationEnvironmental Sound Classification with Parallel Temporal-spectral Attention
Convolutional neural networks (CNN) are one of the best-performing neural network architectures for environmental sound classification (ESC). Recently, temporal attention mechanisms have been used in CNN to capture the u…
Acoustic Scene ClassificationAudio ClassificationClassificationEnvironmental Sound Classification+3Detection of Adversarial Attacks and Characterization of Adversarial Subspace
Adversarial attacks have always been a serious threat for any data-driven model. In this paper, we explore subspaces of adversarial examples in unitary vector domain, and we propose a novel detector for defending our mod…
BenchmarkingEnvironmental Sound ClassificationregressionSound ClassificationUrban Sound Tagging using Convolutional Neural Networks
In this paper, we propose a framework for environmental sound classification in a low-data context (less than 100 labeled examples per class). We show that using pre-trained image classification models along with the usa…
Data AugmentationEnvironmental Sound ClassificationGeneral Classificationimage-classification+2AI 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 Classification