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Audio Classification

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평가표: 26
보존된 평가 기록: 199

Audio Classification is a machine learning task that involves identifying and tagging audio signals into different classes or categories. The goal of audio classification is to enable machines to automatically recognize and distinguish between different types of audio, such as music, speech, and environmental sounds.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/AlanBaade/MAE-AST-Public

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MAE-AST: Masked Autoencoding Audio Spectrogram Transformer

https://github.com/Alibaba-MIIL/AudioClassfication

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End-to-End Audio Strikes Back: Boosting Augmentations Towards An Efficient Audio Classification Network

https://github.com/AndrewPBerg/UAV_Classification

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4,500 Seconds: Small Data Training Approaches for Deep UAV Audio Classification

https://github.com/AndreyGuzhov/AudioCLIP

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AudioCLIP: Extending CLIP to Image, Text and Audio

https://github.com/AndreyGuzhov/ESResNet

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ESResNet: Environmental Sound Classification Based on Visual Domain Models

https://github.com/Audio-WestlakeU/audiossl/tree/main/audiossl/methods/atst

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ATST: Audio Representation Learning with Teacher-Student Transformer

https://github.com/CPJKU/veracity

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On the Veracity of Local, Model-agnostic Explanations in Audio Classification: Targeted Investigations with Adversarial Examples

https://github.com/Camille112/T-CLAP

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Enhancing Audio-Language Models through Self-Supervised Post-Training with Text-Audio Pairs

https://github.com/DragonLiu1995/Vision-to-Audio-and-Beyond

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From Vision to Audio and Beyond: A Unified Model for Audio-Visual Representation and Generation

https://github.com/Efficient-Scalable-Machine-Learning/event-ssm

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Scalable Event-by-event Processing of Neuromorphic Sensory Signals With Deep State-Space Models

https://github.com/FederatedSTAR/FedSTAR

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Federated Self-Training for Semi-Supervised Audio Recognition

https://github.com/Forsad/Stable-Polynomial-Train

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A Training Framework for Optimal and Stable Training of Polynomial Neural Networks

https://github.com/HolmesShuan/Compact-Global-Descriptor

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Compact Global Descriptor for Neural Networks

https://github.com/HumamAlwassel/XDC

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Self-Supervised Learning by Cross-Modal Audio-Video Clustering

https://github.com/JNAIC/PIPMN

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Effective Audio Classification Network Based on Paired Inverse Pyramid Structure and Dense MLP Block

https://github.com/K-STMLab/SSL4PR

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Exploiting Foundation Models and Speech Enhancement for Parkinson's Disease Detection from Speech in Real-World Operative Conditions

https://github.com/Labbeti/SSLH

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Comparison of semi-supervised deep learning algorithms for audio classification

https://github.com/LorisNanni/Audiogmenter

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Audiogmenter: a MATLAB Toolbox for Audio Data Augmentation

https://github.com/MorenoLaQuatra/ARCH

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Benchmarking Representations for Speech, Music, and Acoustic Events

https://github.com/MrtnMndt/OCDVAEContinualLearning

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Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition

https://github.com/MrtnMndt/OCDVAE_ContinualLearning

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Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition

https://github.com/OFA-Sys/ONE-PEACE

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ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities

https://github.com/PaddlePaddle/PaddleSpeech

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PaddleSpeech: An Easy-to-Use All-in-One Speech Toolkit

https://github.com/ParitoshParmar/Piano-Skills-Assessment

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Piano Skills Assessment

https://github.com/Saurabhbhati/DASS

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DASS: Distilled Audio State Space Models Are Stronger and More Duration-Scalable Learners

https://github.com/SonyCSLParis/audio-representations

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Investigating Design Choices in Joint-Embedding Predictive Architectures for General Audio Representation Learning

https://github.com/Sound2Synth/Sound2Synth

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Sound2Synth: Interpreting Sound via FM Synthesizer Parameters Estimation

https://github.com/Sreyan88/LAPE

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MAST: Multiscale Audio Spectrogram Transformers

https://github.com/Tab-ct/MAP-SNN

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MAP-SNN: Mapping Spike Activities with Multiplicity, Adaptability, and Plasticity into Bio-Plausible Spiking Neural Networks

https://github.com/Tab-ct/STSC-SNN

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STSC-SNN: Spatio-Temporal Synaptic Connection with Temporal Convolution and Attention for Spiking Neural Networks

https://github.com/Westlake-AI/SemiReward

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SemiReward: A General Reward Model for Semi-supervised Learning

https://github.com/YuanGongND/ast

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AST: Audio Spectrogram Transformer

https://github.com/YuanGongND/psla

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PSLA: Improving Audio Tagging with Pretraining, Sampling, Labeling, and Aggregation

https://github.com/YuanGongND/ssast

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SSAST: Self-Supervised Audio Spectrogram Transformer

https://github.com/YuanGongND/uavm

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UAVM: Towards Unifying Audio and Visual Models

https://github.com/YuanGongND/vocalsound

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Vocalsound: A Dataset for Improving Human Vocal Sounds Recognition

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