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Environmental Sound Classification

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크: 1
평가표: 3
보존된 평가 기록: 5

Classification of Environmental Sounds. Most often sounds found in Urban environments. Task related to noise monitoring.

코드

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

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

공식 코드

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

https://github.com/AndreyGuzhov/AudioCLIP

공식 코드

AudioCLIP: Extending CLIP to Image, Text and Audio

https://github.com/AndreyGuzhov/ESResNet

공식 코드

ESResNet: Environmental Sound Classification Based on Visual Domain Models

https://github.com/JNAIC/PIPMN

공식 코드

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

https://github.com/Labbeti/SSLH

공식 코드

Comparison of semi-supervised deep learning algorithms for audio classification

https://github.com/PaddlePaddle/PaddleSpeech

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

https://github.com/ai-techsystems/deepC

공식 코드

Tiny Transformers for Environmental Sound Classification at the Edge

https://github.com/alireza-nasiri/SoundCLR

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SoundCLR: Contrastive Learning of Representations For Improved Environmental Sound Classification

https://github.com/chenhao1umbc/WSCDL

공식 코드

Weakly Supervised Convolutional Dictionary Learning for Multi-Label Classification

https://github.com/corticph/MSTmodel

공식 코드

Utilizing Domain Knowledge in End-to-End Audio Processing

https://github.com/eacevedo1/audiotext-contextda

공식 코드

Domain Adaptation Method and Modality Gap Impact in Audio-Text Models for Prototypical Sound Classification

https://github.com/fadymedhat/MCLNN

공식 코드

Masked Conditional Neural Networks for Environmental Sound Classification

https://github.com/fadymedhat/YorNoise

공식 코드

Masked Conditional Neural Networks for Environmental Sound Classification

https://github.com/gitmehrdad/face

공식 코드

Face: Fast, Accurate and Context-Aware Audio Annotation and Classification

https://github.com/jonahanton/ssl_audio

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Audio Barlow Twins: Self-Supervised Audio Representation Learning

https://github.com/justinsalamon/UrbanSound8K-JAMS

공식 코드

Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification

https://github.com/kamalesh0406/Audio-Classification

공식 코드

Rethinking CNN Models for Audio Classification

https://github.com/mohaimenz/acdnet

공식 코드

Environmental Sound Classification on the Edge: A Pipeline for Deep Acoustic Networks on Extremely Resource-Constrained Devices

https://github.com/multitel-ai/urban-sound-classification-and-comparison

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Urban Sound Classification : striving towards a fair comparison

https://github.com/multitel-ai/urban-sound-tagging

공식 코드

CRNNs for Urban Sound Tagging with spatiotemporal context

https://github.com/pritamqu/CrissCross

공식 코드

Self-Supervised Audio-Visual Representation Learning with Relaxed Cross-Modal Synchronicity

https://github.com/sainathadapa/urban-sound-tagging

공식 코드

Urban Sound Tagging using Convolutional Neural Networks

https://github.com/sajabdoli/Environmental_sound_classification

공식 코드

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

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

공식 코드

Continual Learning For On-Device Environmental Sound Classification

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