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Audio Classification

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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/sajabdoli/Environmental_sound_classification

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End-to-End Environmental Sound Classification using a 1D Convolutional Neural Network

https://github.com/satvik-venkatesh/audio-seg-data-synth

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Artificially Synthesising Data for Audio Classification and Segmentation to Improve Speech and Music Detection in Radio Broadcast

https://github.com/sebraun-msr/acd_class_mapping

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Multi-label audio classification with a noisy zero-shot teacher

https://github.com/shijing001/unicertainty_calibration_audio_classifiers

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Uncertainty Calibration for Deep Audio Classifiers

https://github.com/siavashshams/ssamba

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SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model

https://github.com/soerenab/AudioMNIST

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AudioMNIST: Exploring Explainable Artificial Intelligence for Audio Analysis on a Simple Benchmark

https://github.com/sreyan88/reclap

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ReCLAP: Improving Zero Shot Audio Classification by Describing Sounds

https://github.com/sreyan88/synthio

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Synthio: Augmenting Small-Scale Audio Classification Datasets with Synthetic Data

https://github.com/swagshaw/asc-cl

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Continual Learning For On-Device Environmental Sound Classification

https://github.com/swarupbehera/FastAST

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FastAST: Accelerating Audio Spectrogram Transformer via Token Merging and Cross-Model Knowledge Distillation

https://github.com/synsense/rockpool

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Sub-mW Neuromorphic SNN audio processing applications with Rockpool and Xylo

https://github.com/themoro/diraugmentation

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Device-Robust Acoustic Scene Classification via Impulse Response Augmentation

https://github.com/thomeou/SALSA

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DCASE 2021 Task 3: Spectrotemporally-aligned Features for Polyphonic Sound Event Localization and Detection

https://github.com/thvnvtos/snn-delays

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Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings

https://github.com/tqbl/ood_audio

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Learning with Out-of-Distribution Data for Audio Classification

https://github.com/turab45/audrandaug

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AudRandAug: Random Image Augmentations for Audio Classification

https://github.com/umbertocappellazzo/petl_ast

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Parameter-Efficient Transfer Learning of Audio Spectrogram Transformers

https://github.com/verivital/nnv

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Formal Verification of Long Short-Term Memory based Audio Classifiers: A Star based Approach

https://github.com/vinceasvp/fcac

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Few-shot Class-incremental Audio Classification Using Dynamically Expanded Classifier with Self-attention Modified Prototypes

https://github.com/vinceasvp/meta-sc

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Few-shot Class-incremental Audio Classification Using Stochastic Classifier

https://github.com/wa976/pafa

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Patient-Aware Feature Alignment for Robust Lung Sound Classification:Cohesion-Separation and Global Alignment Losses

https://github.com/webstorms/fastsnn

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Robust and accelerated single-spike spiking neural network training with applicability to challenging temporal tasks

https://github.com/yongjiesi/ede

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Fully Few-shot Class-incremental Audio Classification Using Expandable Dual-embedding Extractor

https://github.com/yongjiesi/mar

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Fully Few-shot Class-incremental Audio Classification Using Multi-level Embedding Extractor and Ridge Regression Classifier

https://github.com/yuangongnd/cav-mae

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Contrastive Audio-Visual Masked Autoencoder

https://github.com/zdsy/proto-MAML

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Episodic fine-tuning prototypical networks for optimization-based few-shot learning: Application to audio classification

https://github.com/zhaoyanpeng/vipant

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Connecting the Dots between Audio and Text without Parallel Data through Visual Knowledge Transfer

https://github.com/zpforlove/rene

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Rene: A Pre-trained Multi-modal Architecture for Auscultation of Respiratory Diseases

https://github.com/2023-MindSpore-4/Code8/tree/main/ats

ATST: Audio Representation Learning with Teacher-Student Transformer

https://github.com/2024-MindSpore-1/Code6/tree/main/ats

ATST: Audio Representation Learning with Teacher-Student Transformer

https://github.com/Audio-WestlakeU/ATST-SED

ATST: Audio Representation Learning with Teacher-Student Transformer

https://github.com/CHeggan/Few-Shot-Classification-for-Audio-Evaluation

On the Transferability of Large-Scale Self-Supervision to Few-Shot Audio Classification

https://github.com/HeleneFabia/keyword-spotter

Rethinking CNN Models for Audio Classification

https://github.com/IBM/MAX-Audio-Classifier

CNN Architectures for Large-Scale Audio Classification

https://github.com/IBM/MAX-Audio-Embedding-Generator

CNN Architectures for Large-Scale Audio Classification

https://github.com/IBM/audioset-classification

Multi-level Attention Model for Weakly Supervised Audio Classification

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