Papers Sound Classification
“Sound Classification” 태그가 달린 논문 148편 · 필터 해제
EAT: Self-Supervised Pre-Training with Efficient Audio Transformer
Audio self-supervised learning (SSL) pre-training, which aims to learn good representations from unlabeled audio, has made remarkable progress. However, the extensive computational demands during pre-training pose a sign…
Audio ClassificationSelf-Supervised LearningSound ClassificationSelf-Supervised Learning for Few-Shot Bird Sound Classification
Self-supervised learning (SSL) in audio holds significant potential across various domains, particularly in situations where abundant, unlabeled data is readily available at no cost. This is pertinent in bioacoustics, wh…
ClassificationFew-Shot LearningSelf-Supervised LearningSound ClassificationStethoscope-guided Supervised Contrastive Learning for Cross-domain Adaptation on Respiratory Sound Classification
Despite the remarkable advances in deep learning technology, achieving satisfactory performance in lung sound classification remains a challenge due to the scarcity of available data. Moreover, the respiratory sound samp…
Audio ClassificationContrastive LearningDomain AdaptationLung Sound Classification+1Multi-View Spectrogram Transformer for Respiratory Sound Classification
Deep neural networks have been applied to audio spectrograms for respiratory sound classification. Existing models often treat the spectrogram as a synthetic image while overlooking its physical characteristics. In this …
ClassificationSound ClassificationAdversarial Fine-tuning using Generated Respiratory Sound to Address Class Imbalance
Deep generative models have emerged as a promising approach in the medical image domain to address data scarcity. However, their use for sequential data like respiratory sounds is less explored. In this work, we propose …
Audio ClassificationSound ClassificationFeature Aggregation in Joint Sound Classification and Localization Neural Networks
This study addresses the application of deep learning techniques in joint sound signal classification and localization networks. Current state-of-the-art sound source localization deep learning networks lack feature aggr…
regressionSound ClassificationSound Event Localization and DetectionSound Source LocalizationCodec Data Augmentation for Time-domain Heart Sound Classification
Heart auscultations are a low-cost and effective way of detecting valvular heart diseases early, which can save lives. Nevertheless, it has been difficult to scale this screening method since the effectiveness of auscult…
ClassificationData AugmentationSound ClassificationEchoVest: Real-Time Sound Classification and Depth Perception Expressed through Transcutaneous Electrical Nerve Stimulation
Over 1.5 billion people worldwide live with hearing impairment. Despite various technologies that have been created for individuals with such disabilities, most of these technologies are either extremely expensive or ina…
blind source separationClassificationEnvironmental Sound ClassificationSound ClassificationAsTFSONN: A Unified Framework Based on Time-Frequency Domain Self-Operational Neural Network for Asthmatic Lung Sound Classification
Asthma is one of the most severe chronic respiratory diseases which can be diagnosed using several modalities, such as lung function test or spirometric measures, peak flow meter-based measures, sputum eosinophils, patho…
Asthmatic Lung Sound ClassificationAudio ClassificationDiagnosticLung Disease Classification+3Channel-Spatial-Based Few-Shot Bird Sound Event Detection
In this paper, we propose a model for bird sound event detection that focuses on a small number of training samples within the everyday long-tail distribution. As a result, we investigate bird sound detection using the f…
Event DetectionFew-Shot LearningSound ClassificationSound Event DetectionCorrelation Clustering of Bird Sounds
Bird sound classification is the task of relating any sound recording to those species of bird that can be heard in the recording. Here, we study bird sound clustering, the task of deciding for any pair of sound recordin…
ClassificationClusteringSound ClassificationPatch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification
Respiratory sound contains crucial information for the early diagnosis of fatal lung diseases. Since the COVID-19 pandemic, there has been a growing interest in contact-free medical care based on electronic stethoscopes.…
Audio ClassificationContrastive LearningSound ClassificationFeature-Rich Audio Model Inversion for Data-Free Knowledge Distillation Towards General Sound Classification
Data-Free Knowledge Distillation (DFKD) has recently attracted growing attention in the academic community, especially with major breakthroughs in computer vision. Despite promising results, the technique has not been we…
Data-free Knowledge DistillationKnowledge DistillationSound ClassificationFace: Fast, Accurate and Context-Aware Audio Annotation and Classification
This paper presents a context-aware framework for feature selection and classification procedures to realize a fast and accurate audio event annotation and classification. The context-aware design starts with exploring f…
Active LearningAudio ClassificationClassificationEnvironmental Sound Classification+3Unsupervised classification to improve the quality of a bird song recording dataset
Open audio databases such as Xeno-Canto are widely used to build datasets to explore bird song repertoire or to train models for automatic bird sound classification by deep learning algorithms. However, such databases su…
Sound ClassificationTemporal LocalizationA dataset for Audio-Visual Sound Event Detection in Movies
Audio event detection is a widely studied audio processing task, with applications ranging from self-driving cars to healthcare. In-the-wild datasets such as Audioset have propelled research in this field. However, many …
Event DetectionSelf-Driving CarsSound ClassificationSound Event DetectionEpic-Sounds: A Large-scale Dataset of Actions That Sound
We introduce Epic-Sounds, a large-scale dataset of audio annotations capturing temporal extents and class labels within the audio stream of the egocentric videos. We propose an annotation pipeline where annotators tempor…
Action RecognitionSound ClassificationXKD: Cross-modal Knowledge Distillation with Domain Alignment for Video Representation Learning
We present XKD, a novel self-supervised framework to learn meaningful representations from unlabelled videos. XKD is trained with two pseudo objectives. First, masked data reconstruction is performed to learn modality-sp…
Action ClassificationClassificationKnowledge DistillationRepresentation Learning+4SpectNet : End-to-End Audio Signal Classification Using Learnable Spectrograms
Pattern recognition from audio signals is an active research topic encompassing audio tagging, acoustic scene classification, music classification, and other areas. Spectrogram and mel-frequency cepstral coefficients (MF…
Acoustic Scene ClassificationAnomaly DetectionAudio ClassificationAudio Tagging+4Exploring the Impact of Noise and Degradations on Heart Sound Classification Models
The development of data-driven heart sound classification models has been an active area of research in recent years. To develop such data-driven models in the first place, heart sound signals need to be captured using a…
ClassificationSound Classification