Papers Sound Classification
“Sound Classification” 태그가 달린 논문 148편 · 필터 해제
Classification of Adventitious Sounds Combining Cochleogram and Vision Transformers
Early identification of respiratory irregularities is critical for improving lung health and reducing global mortality rates. The analysis of respiratory sounds plays a significant role in characterizing the respiratory …
Audio ClassificationClassificationSound ClassificationUnsupervised detection and classification of heartbeats using the dissimilarity matrix in PCG signals
The proposed system consists of a two-stage cascade. The first stage performs a rough heartbeat detection while the second stage refines the previous one, improving the temporal localization and also classifying the hear…
Heart SegmentationSound ClassificationTemporal LocalizationManikin-Recorded Cardiopulmonary Sounds Dataset Using Digital Stethoscope
Heart and lung sounds are crucial for healthcare monitoring. Recent improvements in stethoscope technology have made it possible to capture patient sounds with enhanced precision. In this dataset, we used a digital steth…
Audio Signal ProcessingSound ClassificationHeterogeneous sound classification with the Broad Sound Taxonomy and Dataset
Automatic sound classification has a wide range of applications in machine listening, enabling context-aware sound processing and understanding. This paper explores methodologies for automatically classifying heterogeneo…
ClassificationSound ClassificationECHO: Environmental Sound Classification with Hierarchical Ontology-guided Semi-Supervised Learning
Environment Sound Classification has been a well-studied research problem in the field of signal processing and up till now more focus has been laid on fully supervised approaches. Over the last few years, focus has move…
Contrastive LearningEnvironmental Sound ClassificationEnvironment Sound ClassificationLanguage Modeling+3Generalization in birdsong classification: impact of transfer learning methods and dataset characteristics
Animal sounds can be recognised automatically by machine learning, and this has an important role to play in biodiversity monitoring. Yet despite increasingly impressive capabilities, bioacoustic species classifiers stil…
Knowledge DistillationSound ClassificationTransfer LearningBUET Multi-disease Heart Sound Dataset: A Comprehensive Auscultation Dataset for Developing Computer-Aided Diagnostic Systems
Cardiac auscultation, an integral tool in diagnosing cardiovascular diseases (CVDs), often relies on the subjective interpretation of clinicians, presenting a limitation in consistency and accuracy. Addressing this, we i…
DiagnosticManagementSound ClassificationStudying the Effect of Audio Filters in Pre-Trained Models for Environmental Sound Classification
Environmental Sound Classification is an important problem of sound recognition and is more complicated than speech recognition problems as environmental sounds are not well structured with respect to time and frequency.…
ClassificationEnvironmental Sound ClassificationSound Classificationspeech-recognition+1Improving the Robustness and Clinical Applicability of Automatic Respiratory Sound Classification Using Deep Learning-Based Audio Enhancement: Algorithm Development and Validation
Deep learning techniques have shown promising results in the automatic classification of respiratory sounds. However, accurately distinguishing these sounds in real-world noisy conditions remains challenging for clinical…
ClassificationData AugmentationDiagnosticSound ClassificationTowards Enhanced Classification of Abnormal Lung sound in Multi-breath: A Light Weight Multi-label and Multi-head Attention Classification Method
This study aims to develop an auxiliary diagnostic system for classifying abnormal lung respiratory sounds, enhancing the accuracy of automatic abnormal breath sound classification through an innovative multi-label learn…
DiagnosticDiversityMulti-Label LearningSound ClassificationAdvanced Framework for Animal Sound Classification With Features Optimization
The automatic classification of animal sounds presents an enduring challenge in bioacoustics, owing to the diverse statistical properties of sound signals, variations in recording equipment, and prevalent low Signal-to-N…
ClassificationDiversitySound Classificationspeech-recognition+1BTS: Bridging Text and Sound Modalities for Metadata-Aided Respiratory Sound Classification
Respiratory sound classification (RSC) is challenging due to varied acoustic signatures, primarily influenced by patient demographics and recording environments. To address this issue, we introduce a text-audio multimoda…
Audio ClassificationSound ClassificationEnhanced Heart Sound Classification Using Mel Frequency Cepstral Coefficients and Comparative Analysis of Single vs. Ensemble Classifier Strategies
This paper explores the efficacy of Mel Frequency Cepstral Coefficients (MFCCs) in detecting abnormal heart sounds using two classification strategies: a single classifier and an ensemble classifier approach. Heart sound…
ClassificationSound ClassificationAttention Feature Fusion Network via Knowledge Propagation for Automated Respiratory Sound Classification
In light of the COVID-19 pandemic, the early diagnosis of respiratory diseases has become increasingly crucial. Traditional diagnostic methods such as computed tomography (CT) and magnetic resonance imaging (MRI), whil…
Audio ClassificationComputed Tomography (CT)Diagnosticimage-classification+2RepAugment: Input-Agnostic Representation-Level Augmentation for Respiratory Sound Classification
Recent advancements in AI have democratized its deployment as a healthcare assistant. While pretrained models from large-scale visual and audio datasets have demonstrably generalized to this task, surprisingly, no studie…
Data AugmentationSound ClassificationAudioProtoPNet: An interpretable deep learning model for bird sound classification
Deep learning models have significantly advanced acoustic bird monitoring by being able to recognize numerous bird species based on their vocalizations. However, traditional deep learning models are black boxes that prov…
Audio ClassificationClassificationDecision MakingDeep Learning+2Classification of Short Segment Pediatric Heart Sounds Based on a Transformer-Based Convolutional Neural Network
Congenital anomalies arising as a result of a defect in the structure of the heart and great vessels are known as congenital heart diseases or CHDs. A PCG can provide essential details about the mechanical conduction sys…
Sound ClassificationSynthetic training set generation using text-to-audio models for environmental sound classification
In recent years, text-to-audio models have revolutionized the field of automatic audio generation. This paper investigates their application in generating synthetic datasets for training data-driven models. Specifically,…
Audio GenerationClassificationEnvironmental Sound ClassificationSound ClassificationTuning In: Analysis of Audio Classifier Performance in Clinical Settings with Limited Data
This study assesses deep learning models for audio classification in a clinical setting with the constraint of small datasets reflecting real-world prospective data collection. We analyze CNNs, including DenseNet and Con…
Audio ClassificationClassificationModel SelectionSound ClassificationFocal Modulation Networks for Interpretable Sound Classification
The increasing success of deep neural networks has raised concerns about their inherent black-box nature, posing challenges related to interpretability and trust. While there has been extensive exploration of interpretat…
ClassificationEnvironmental Sound ClassificationSound Classification