Papers Audio Classification
“Audio Classification” 태그가 달린 논문 413편 · 필터 해제
15,500 Seconds: Lean UAV Classification Leveraging PEFT and Pre-Trained Networks
Unmanned Aerial Vehicles (UAVs) pose an escalating security concerns as the market for consumer and military UAVs grows. This paper address the critical data scarcity challenges in deep UAV audio classification. We build…
Audio ClassificationData Augmentationparameter-efficient fine-tuningLarge Language Models Implicitly Learn to See and Hear Just By Reading
This paper presents a fascinating find: By training an auto-regressive LLM model on text tokens, the text model inherently develops internally an ability to understand images and audio, thereby developing the ability to …
Audio Classificationimage-classificationImage ClassificationA Training Framework for Optimal and Stable Training of Polynomial Neural Networks
By replacing standard non-linearities with polynomial activations, Polynomial Neural Networks (PNNs) are pivotal for applications such as privacy-preserving inference via Homomorphic Encryption (HE). However, training PN…
Audio ClassificationHomomorphic Encryption for Deep LearningHuman Activity RecognitionImage Classification+2Can Masked Autoencoders Also Listen to Birds?
Masked Autoencoders (MAEs) have shown competitive results in audio classification by learning rich semantic representations through an efficient self-supervised reconstruction task. However, general-purpose models fail t…
Audio ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONSelf-Supervised Learning+1Progressive Rock Music Classification
This study investigates the classification of progressive rock music, a genre characterized by complex compositions and diverse instrumentation, distinct from other musical styles. Addressing this Music Information Retri…
Audio ClassificationClassificationDimensionality ReductionGenre classification+3Token Pruning in Audio Transformers: Optimizing Performance and Decoding Patch Importance
Vision Transformers (ViTs) have achieved state-of-the-art performance across various computer vision tasks, but their high computational cost remains a challenge. Token pruning has been proposed to reduce this cost by se…
Audio ClassificationCA^2ST: Cross-Attention in Audio, Space, and Time for Holistic Video Recognition
We propose Cross-Attention in Audio, Space, and Time (CA^2ST), a transformer-based method for holistic video recognition. Recognizing actions in videos requires both spatial and temporal understanding, yet most existing …
Action ClassificationAction RecognitionAudio ClassificationVideo Recognition+1M2D2: Exploring General-purpose Audio-Language Representations Beyond CLAP
Contrastive language-audio pre-training (CLAP) has addressed audio-language tasks such as audio-text retrieval by aligning audio and text in a common feature space. While CLAP addresses general audio-language tasks, its …
Audio captioningAudio ClassificationAudio TaggingAudio to Text Retrieval+13Symbolic Audio Classification via Modal Decision Tree Learning
The range of potential applications of acoustic analysis is wide. Classification of sounds, in particular, is a typical machine learning task that received a lot of attention in recent years. The most common approaches t…
Audio ClassificationClassificationEmotion ClassificationSound ClassificationFundamental Survey on Neuromorphic Based Audio Classification
Audio classification is paramount in a variety of applications including surveillance, healthcare monitoring, and environmental analysis. Traditional methods frequently depend on intricate signal processing algorithms an…
Audio ClassificationClassificationComputational EfficiencySurveyMasked Latent Prediction and Classification for Self-Supervised Audio Representation Learning
Recently, self-supervised learning methods based on masked latent prediction have proven to encode input data into powerful representations. However, during training, the learned latent space can be further transformed t…
Audio ClassificationAudio TaggingClassificationEnvironmental Sound Classification+9CycleGuardian: A Framework for Automatic RespiratorySound classification Based on Improved Deep clustering and Contrastive Learning
Auscultation plays a pivotal role in early respiratory and pulmonary disease diagnosis. Despite the emergence of deep learning-based methods for automatic respiratory sound classification post-Covid-19, limited datasets …
Audio ClassificationClusteringConstrained ClusteringContrastive Learning+2LHGNN: Local-Higher Order Graph Neural Networks For Audio Classification and Tagging
Transformers have set new benchmarks in audio processing tasks, leveraging self-attention mechanisms to capture complex patterns and dependencies within audio data. However, their focus on pairwise interactions limits th…
Audio ClassificationGraph Neural NetworkTSPE: Task-Specific Prompt Ensemble for Improved Zero-Shot Audio Classification
Audio-language models (ALMs) excel in zero-shot audio classification, a task where models classify previously unseen audio clips at test time by leveraging descriptive natural language prompts. We introduce TSPE (Task-Sp…
Audio ClassificationClassificationDescriptiveZero-shot Audio ClassificationDomain-Incremental Learning for Audio Classification
In this work, we propose a method for domain-incremental learning for audio classification from a sequence of datasets recorded in different acoustic conditions. Fine-tuning a model on a sequence of evolving domains or d…
Audio ClassificationClassificationIncremental LearningMulti-Label Classification+1Continual Low-Rank Scaled Dot-product Attention
Transformers are widely used for their ability to capture data relations in sequence processing, with great success for a wide range of static tasks. However, the computational and memory footprint of their main componen…
Action DetectionAudio ClassificationOnline Action DetectionRaw Audio Classification with Cosine Convolutional Neural Network (CosCovNN)
This study explores the field of audio classification from raw waveform using Convolutional Neural Networks (CNNs), a method that eliminates the need for extracting specialised features in the pre-processing step. Unlike…
Audio ClassificationSTREAM: A Universal State-Space Model for Sparse Geometric Data
Handling sparse and unstructured geometric data, such as point clouds or event-based vision, is a pressing challenge in the field of machine vision. Recently, sequence models such as Transformers and state-space models e…
Audio ClassificationEvent-based visionInductive BiasMamba+2Classification 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 ClassificationPerformance Analysis of Hybrid Quantum-Classical Convolutional Neural Networks for Audio Classification
Audio signals being high-dimensional and complex pose challenges for classical machine learning techniques in terms of computation and generalization on real-world data. This paper evaluates the use of hybrid quantum-cla…
Audio ClassificationQuantum Machine Learning