Papers Audio Classification
“Audio Classification” 태그가 달린 논문 413편 · 필터 해제
Simple Pooling Front-ends For Efficient Audio Classification
Recently, there has been increasing interest in building efficient audio neural networks for on-device scenarios. Most existing approaches are designed to reduce the size of audio neural networks using methods such as mo…
Audio ClassificationClassificationContrastive Audio-Visual Masked Autoencoder
In this paper, we first extend the recent Masked Auto-Encoder (MAE) model from a single modality to audio-visual multi-modalities. Subsequently, we propose the Contrastive Audio-Visual Masked Auto-Encoder (CAV-MAE) by co…
Audio ClassificationAudio TaggingContrastive LearningMulti-modal Classification+4AVT: Audio-Video Transformer for Multimodal Action Recognition
Action recognition is an essential field for video understanding. To learn from heterogeneous data sources effectively, in this work, we propose a novel multimodal action recognition approach termed Audio-Video Transform…
Action RecognitionAudio ClassificationContrastive LearningMulti-modal Classification+1Multiscale Multimodal Transformer for Multimodal Action Recognition
While action recognition has been an active research area for several years, most existing approaches merely leverage the video modality as opposed to humans that efficiently process video and audio cues simultaneously. …
Action RecognitionAudio ClassificationMulti-modal ClassificationRepresentation LearningInvestigating current-based and gating approaches for accurate and energy-efficient spiking recurrent neural networks
Spiking Neural Networks (SNNs) with spike-based computations and communications may be more energy-efficient than Artificial Neural Networks (ANNs) for embedded applications. However, SNNs have mostly been applied to ima…
Audio ClassificationTemporal SequencesImproving the Environmental Perception of Autonomous Vehicles using Deep Learning-based Audio Classification
Sense of hearing is crucial for autonomous vehicles (AVs) to better perceive its surrounding environment. Although visual sensors of an AV, such as camera, lidar, and radar, help to see its surrounding environment, an AV…
Audio ClassificationAutonomous VehiclesClassificationAudio Analytics-based Human Trafficking Detection Framework for Autonomous Vehicles
Human trafficking is a universal problem, persistent despite numerous efforts to combat it globally. Individuals of any age, race, ethnicity, sex, gender identity, sexual orientation, nationality, immigration status, cul…
Audio ClassificationAutonomous VehiclesHardware Accelerator and Neural Network Co-Optimization for Ultra-Low-Power Audio Processing Devices
The increasing spread of artificial neural networks does not stop at ultralow-power edge devices. However, these very often have high computational demand and require specialized hardware accelerators to ensure the desig…
Action DetectionActivity DetectionAudio ClassificationSub-mW Neuromorphic SNN audio processing applications with Rockpool and Xylo
Spiking Neural Networks (SNNs) provide an efficient computational mechanism for temporal signal processing, especially when coupled with low-power SNN inference ASICs. SNNs have been historically difficult to configure, …
Audio ClassificationA Study on Broadcast Networks for Music Genre Classification
Due to the increased demand for music streaming/recommender services and the recent developments of music information retrieval frameworks, Music Genre Classification (MGC) has attracted the community's attention. Howeve…
Audio ClassificationClassificationGenre classificationInformation Retrieval+3A surrogate gradient spiking baseline for speech command recognition
Artificial neural networks (ANNs) are the basis of recent advances in artificial intelligence (AI); they typically use real valued neuron responses. By contrast, biological neurons are known to operate using spike trains…
Audio ClassificationTime SeriesDeep Feature Learning for Medical Acoustics
The purpose of this paper is to compare different learnable frontends in medical acoustics tasks. A framework has been implemented to classify human respiratory sounds and heartbeats in two categories, i.e. healthy or af…
Audio ClassificationUAVM: Towards Unifying Audio and Visual Models
Conventional audio-visual models have independent audio and video branches. In this work, we unify the audio and visual branches by designing a Unified Audio-Visual Model (UAVM). The UAVM achieves a new state-of-the-art …
Audio Classificationaudio-visual learningMulti-modal ClassificationMasked Autoencoders that Listen
This paper studies a simple extension of image-based Masked Autoencoders (MAE) to self-supervised representation learning from audio spectrograms. Following the Transformer encoder-decoder design in MAE, our Audio-MAE fi…
Audio ClassificationDecoderRepresentation LearningSpeaker IdentificationEfficientLEAF: A Faster LEarnable Audio Frontend of Questionable Use
In audio classification, differentiable auditory filterbanks with few parameters cover the middle ground between hard-coded spectrograms and raw audio. LEAF (arXiv:2101.08596), a Gabor-based filterbank combined with Per-…
Audio ClassificationClassificationInstrument RecognitionPitch Classification+1Western Mediterranean wetlands bird species classification: evaluating small-footprint deep learning approaches on a new annotated dataset
The deployment of an expert system running over a wireless acoustic sensors network made up of bioacoustic monitoring devices that recognise bird species from their sounds would enable the automation of many tasks of eco…
Audio ClassificationUncertainty Calibration for Deep Audio Classifiers
Although deep Neural Networks (DNNs) have achieved tremendous success in audio classification tasks, their uncertainty calibration are still under-explored. A well-calibrated model should be accurate when it is certain a…
Audio ClassificationClassificationGenre classificationMusic Genre ClassificationFluctuation-driven initialization for spiking neural network training
Spiking neural networks (SNNs) underlie low-power, fault-tolerant information processing in the brain and could constitute a power-efficient alternative to conventional deep neural networks when implemented on suitable n…
Audio Classification0/1 Deep Neural Networks via Block Coordinate Descent
The step function is one of the simplest and most natural activation functions for deep neural networks (DNNs). As it counts 1 for positive variables and 0 for others, its intrinsic characteristics (e.g., discontinuity a…
10-shot image generation16k2D Object Detection+92Binary Early-Exit Network for Adaptive Inference on Low-Resource Devices
Deep neural networks have significantly improved performance on a range of tasks with the increasing demand for computational resources, leaving deployment on low-resource devices (with limited memory and battery power) …
Audio Classification