Papers Sound Classification
“Sound Classification” 태그가 달린 논문 148편 · 필터 해제
Contrastive Learning of Global and Local Video Representations
Contrastive learning has delivered impressive results for various tasks in the self-supervised regime. However, existing approaches optimize for learning representations specific to downstream scenarios, i.e., global rep…
ClassificationContrastive LearningDeepFake DetectionFace Swapping+2Responding 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 ClassificationInterpreting deep urban sound classification using Layer-wise Relevance Propagation
After constructing a deep neural network for urban sound classification, this work focuses on the sensitive application of assisting drivers suffering from hearing loss. As such, clear etiology justifying and interpretin…
ClassificationSound ClassificationSelf-Supervised Audio-Visual Representation Learning with Relaxed Cross-Modal Synchronicity
We present CrissCross, a self-supervised framework for learning audio-visual representations. A novel notion is introduced in our framework whereby in addition to learning the intra-modal and standard 'synchronous' cross…
Audio ClassificationRetrievalSelf-Supervised Action RecognitionSelf-Supervised Audio Classification+4Differentiable Tracking-Based Training of Deep Learning Sound Source Localizers
Data-based and learning-based sound source localization (SSL) has shown promising results in challenging conditions, and is commonly set as a classification or a regression problem. Regression-based approaches have certa…
ClassificationDeep LearningDirection of Arrival Estimationregression+2LungAttn: advanced lung sound classification using attention mechanism with dual TQWT and triple STFT spectrogram
Objective. Auscultation of lung sound plays an important role in the early diagnosis of lung diseases. This work aims to develop an automated adventitious lung sound detection method to reduce the workload of physicians.…
Audio ClassificationLung Sound ClassificationSound ClassificationSpecificityA 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+1Unsupervised Learning of Deep Features for Music Segmentation
Music segmentation refers to the dual problem of identifying boundaries between, and labeling, distinct music segments, e.g., the chorus, verse, bridge etc. in popular music. The performance of a range of music segmentat…
SegmentationSound ClassificationNeonatal Bowel Sound Detection Using Convolutional Neural Network and Laplace Hidden Semi-Markov Model
Abdominal auscultation is a convenient, safe and inexpensive method to assess bowel conditions, which is essential in neonatal care. It helps early detection of neonatal bowel dysfunctions and allows timely intervention.…
Sound ClassificationSegmentation-free Heart Pathology Detection Using Deep Learning
Cardiovascular (CV) diseases are the leading cause of death in the world, and auscultation is typically an essential part of a cardiovascular examination. The ability to diagnose a patient based on their heart sounds is …
Deep LearningSegmentationSound ClassificationLung Sound Classification Using Co-tuning and Stochastic Normalization
In this paper, we use pre-trained ResNet models as backbone architectures for classification of adventitious lung sounds and respiratory diseases. The knowledge of the pre-trained model is transferred by using vanilla fi…
Audio ClassificationData AugmentationLung Sound ClassificationSound ClassificationA Multi-Head Relevance Weighting Framework For Learning Raw Waveform Audio Representations
In this work, we propose a multi-head relevance weighting framework to learn audio representations from raw waveforms. The audio waveform, split into windows of short duration, are processed with a 1-D convolutional laye…
Audio ClassificationSound ClassificationA Visual Domain Transfer Learning Approach for Heartbeat Sound Classification
Heart disease is the most common reason for human mortality that causes almost one-third of deaths throughout the world. Detecting the disease early increases the chances of survival of the patient and there are several …
Classificationdomain classificationSound ClassificationTransfer LearningAudioCLIP: 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 ClassificationDeep Neural Network Based Respiratory Pathology Classification Using Cough Sounds
Intelligent systems are transforming the world, as well as our healthcare system. We propose a deep learning-based cough sound classification model that can distinguish between children with healthy versus pathological c…
ClassificationSound ClassificationZero-Shot Federated Learning with New Classes for Audio Classification
Federated learning is an effective way of extracting insights from different user devices while preserving the privacy of users. However, new classes with completely unseen data distributions can stream across any device…
Audio ClassificationClassificationClusteringFederated Learning+2Heart Sound Classification Considering Additive Noise and Convolutional Distortion
Cardiac auscultation is an essential point-of-care method used for the early diagnosis of heart diseases. Automatic analysis of heart sounds for abnormality detection is faced with the challenges of additive noise and se…
Anomaly DetectionClassificationSound ClassificationSpecificityCrackle Detection In Lung Sounds Using Transfer Learning And Multi-Input Convolitional Neural Networks
Large annotated lung sound databases are publicly available and might be used to train algorithms for diagnosis systems. However, it might be a challenge to develop a well-performing algorithm for small non-public data, …
Lung Sound ClassificationSound ClassificationTransfer LearningEnvGAN: 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 ClassificationContrastive Learning of Global-Local Video Representations
Contrastive learning has delivered impressive results for various tasks in the self-supervised regime. However, existing approaches optimize for learning representations specific to downstream scenarios, i.e., \textit{gl…
ClassificationContrastive LearningDeepFake DetectionFace Swapping+4