Papers Audio Classification
“Audio Classification” 태그가 달린 논문 413편 · 필터 해제
Scalable Event-by-event Processing of Neuromorphic Sensory Signals With Deep State-Space Models
Event-based sensors are well suited for real-time processing due to their fast response times and encoding of the sensory data as successive temporal differences. These and other valuable properties, such as a high dynam…
Audio ClassificationGesture RecognitionHand-Gesture RecognitionState Space ModelsLeveraging tropical reef, bird and unrelated sounds for superior transfer learning in marine bioacoustics
Machine learning has the potential to revolutionize passive acoustic monitoring (PAM) for ecological assessments. However, high annotation and compute costs limit the field's efficacy. Generalizable pretrained networks c…
Audio ClassificationTransfer LearningAudioProtoPNet: 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+2MAX-AST: COMBINING CONVOLUTION, LOCAL AND GLOBAL SELF-ATTENTIONS FOR AUDIO EVENT CLASSIFICATION
In the domain of audio transformer architectures, prior research has extensively investigated isotropic architectures that capture the global context through full self-attention and hierarchical architectures that prog…
Audio ClassificationAudio-Visual Generalized Zero-Shot Learning using Pre-Trained Large Multi-Modal Models
Audio-visual zero-shot learning methods commonly build on features extracted from pre-trained models, e.g. video or audio classification models. However, existing benchmarks predate the popularization of large multi-moda…
Audio ClassificationGeneralized Zero-Shot LearningZero-Shot LearningnEMO: Dataset of Emotional Speech in Polish
Speech emotion recognition has become increasingly important in recent years due to its potential applications in healthcare, customer service, and personalization of dialogue systems. However, a major issue in this fiel…
Audio ClassificationEmotion RecognitionSpeech Emotion RecognitionMasked Modeling Duo: Towards a Universal Audio Pre-training Framework
Self-supervised learning (SSL) using masked prediction has made great strides in general-purpose audio representation. This study proposes Masked Modeling Duo (M2D), an improved masked prediction SSL, which learns by pre…
Audio ClassificationDenoisingEnvironment Sound Classification+3DTF-AT: Decoupled Time-Frequency Audio Transformer for Event Classification
Convolutional neural networks (CNNs) and Transformer-based networks have recently enjoyed significant attention for various audio classification and tagging tasks following their wide adoption in the computer vision doma…
Audio ClassificationInformation RetrievalInternVideo2: Scaling Foundation Models for Multimodal Video Understanding
We introduce InternVideo2, a new family of video foundation models (ViFM) that achieve the state-of-the-art results in video recognition, video-text tasks, and video-centric dialogue. Our core design is a progressive tra…
Action ClassificationAction RecognitionAudio ClassificationContrastive Learning+13BirdSet: A Large-Scale Dataset for Audio Classification in Avian Bioacoustics
Deep learning (DL) has greatly advanced audio classification, yet the field is limited by the scarcity of large-scale benchmark datasets that have propelled progress in other domains. While AudioSet is a pivotal step to …
Audio ClassificationClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+1EquiAV: Leveraging Equivariance for Audio-Visual Contrastive Learning
Recent advancements in self-supervised audio-visual representation learning have demonstrated its potential to capture rich and comprehensive representations. However, despite the advantages of data augmentation verified…
Audio Classificationaudio-visual learningContrastive LearningData Augmentation+1Mixer is more than just a model
Recently, MLP structures have regained popularity, with MLP-Mixer standing out as a prominent example. In the field of computer vision, MLP-Mixer is noted for its ability to extract data information from both channel and…
Audio ClassificationEnvironmental Sound ClassificationmodelSpeech Emotion RecognitionLeveraging Pre-Trained Autoencoders for Interpretable Prototype Learning of Music Audio
We present PECMAE, an interpretable model for music audio classification based on prototype learning. Our model is based on a previous method, APNet, which jointly learns an autoencoder and a prototypical network. Instea…
Audio ClassificationDecoderTuning 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 ClassificationOn the Transferability of Large-Scale Self-Supervision to Few-Shot Audio Classification
In recent years, self-supervised learning has excelled for its capacity to learn robust feature representations from unlabelled data. Networks pretrained through self-supervision serve as effective feature extractors for…
Audio ClassificationFew-Shot Audio ClassificationFew-Shot LearningSelf-Supervised LearningFrom Coarse to Fine: Efficient Training for Audio Spectrogram Transformers
Transformers have become central to recent advances in audio classification. However, training an audio spectrogram transformer, e.g. AST, from scratch can be resource and time-intensive. Furthermore, the complexity of t…
Audio ClassificationLearning Audio Concepts from Counterfactual Natural Language
Conventional audio classification relied on predefined classes, lacking the ability to learn from free-form text. Recent methods unlock learning joint audio-text embeddings from raw audio-text pairs describing audio in n…
Audio captioningAudio ClassificationcounterfactualRetrievalClass-Incremental Learning for Multi-Label Audio Classification
In this paper, we propose a method for class-incremental learning of potentially overlapping sounds for solving a sequence of multi-label audio classification tasks. We design an incremental learner that learns new class…
Audio ClassificationClassificationclass-incremental learningClass Incremental Learning+3EAT: 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 ClassificationOceanship: A Large-Scale Dataset for Underwater Audio Target Recognition
The recognition of underwater audio plays a significant role in identifying a vessel while it is in motion. Underwater target recognition tasks have a wide range of applications in areas such as marine environmental prot…
AttributeAudio ClassificationClassificationRetrieval+2