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Acoustic Scene Classification

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평가표: 5
보존된 평가 기록: 6

The goal of acoustic scene classification is to classify a test recording into one of the provided predefined classes that characterizes the environment in which it was recorded.

Source: DCASE 2019 Source: DCASE 2018

코드

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

https://github.com/Arshdeep-Singh-Boparai/passive-filter-pruning-Interspeech22

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A Passive Similarity based CNN Filter Pruning for Efficient Acoustic Scene Classification

https://github.com/CPJKU/dcase2024_task1_baseline

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Data-Efficient Low-Complexity Acoustic Scene Classification in the DCASE 2024 Challenge

https://github.com/Jungjee/DcaseNet

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DCASENET: A joint pre-trained deep neural network for detecting and classifying acoustic scenes and events

https://github.com/MihawkHu/DCASE2020_task1

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Device-Robust Acoustic Scene Classification Based on Two-Stage Categorization and Data Augmentation

https://github.com/NVIDIA/audio-flamingo

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Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities

https://github.com/OptimusPrimus/dcase2019_task1b

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Exploiting Parallel Audio Recordings to Enforce Device Invariance in CNN-based Acoustic Scene Classification

https://github.com/SRPOL-AUI/spectrum-correction

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Spectrum Correction: Acoustic Scene Classification with Mismatched Recording Devices

https://github.com/ShawMask/congater_dcase2022t1

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Domain Information Control at Inference Time for Acoustic Scene Classification

https://github.com/Shubhajit412/ACOUSTIC_SCENE_CLASSIFICATION_USING_AUDITORY_DATASETS

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Acoustic scene classification using auditory datasets

https://github.com/arshdeep-singh-boparai/efficient_similarity_pruning_algo

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Efficient Similarity-based Passive Filter Pruning for Compressing CNNs

https://github.com/cochlearai/cochlscene

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CochlScene: Acquisition of acoustic scene data using crowdsourcing

https://github.com/cpjku/dcase2025_task1_baseline

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Low-Complexity Acoustic Scene Classification with Device Information in the DCASE 2025 Challenge

https://github.com/dr-costas/undaw

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Unsupervised Adversarial Domain Adaptation Based On The Wasserstein Distance For Acoustic Scene Classification

https://github.com/drylbear/soundscapeCityClassification

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City classification from multiple real-world sound scenes

https://github.com/eihw/asc_sharpness

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Bringing the Discussion of Minima Sharpness to the Audio Domain: a Filter-Normalised Evaluation for Acoustic Scene Classification

https://github.com/hackerekcah/distinct-events-asc

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Acoustic Scene Classification by Implicitly Identifying Distinct Sound Events

https://github.com/jakobabesser/icassp_2022_disentanglementasc

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Towards Audio Domain Adaptation for Acoustic Scene Classification using Disentanglement Learning

https://github.com/jessytan/low-complexity-asc

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Low-Complexity Acoustic Scene Classification Using Parallel Attention-Convolution Network

https://github.com/jishengbai/audiolog

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AudioLog: LLMs-Powered Long Audio Logging with Hybrid Token-Semantic Contrastive Learning

https://github.com/jishengbai/icme2024asc

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Description on IEEE ICME 2024 Grand Challenge: Semi-supervised Acoustic Scene Classification under Domain Shift

https://github.com/jordipons/neural-classifiers-with-few-audio

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Training neural audio classifiers with few data

https://github.com/kkoutini/cpjku_dcase19

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Receptive-field-regularized CNN variants for acoustic scene classification

https://github.com/kkoutini/cpjku_dcase20

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Low-Complexity Models for Acoustic Scene Classification Based on Receptive Field Regularization and Frequency Damping

https://github.com/kkoutini/passt

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Efficient Training of Audio Transformers with Patchout

https://github.com/mihawkhu/asc_knowledge_transfer

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A Variational Bayesian Approach to Learning Latent Variables for Acoustic Knowledge Transfer

https://github.com/qwenlm/qwen-audio

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Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models

https://github.com/shayangharib/AUDASC

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Unsupervised adversarial domain adaptation for acoustic scene classification

https://github.com/themoro/diraugmentation

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Device-Robust Acoustic Scene Classification via Impulse Response Augmentation

https://github.com/yuanbo2020/ergl

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Multi-dimensional Edge-based Audio Event Relational Graph Representation Learning for Acoustic Scene Classification

https://github.com/yuwchen/CITISEN

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CITISEN: A Deep Learning-Based Speech Signal-Processing Mobile Application

https://github.com/zhepeiw/clap_curation

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Unsupervised Improvement of Audio-Text Cross-Modal Representations

https://github.com/JiuSenso/SELD-TCN

SELD-TCN: Sound Event Localization & Detection via Temporal Convolutional Networks

https://github.com/KrishnaDN/acoustic-scene-analysis-with-multihead-self-attention

Acoustic scene analysis with multi-head attention networks

https://github.com/OptimusPrimus/dcase2020_workshop

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification

https://github.com/alibaba-damo-academy/FunASR

Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models

https://github.com/andychinka/dcase-challenge

A multi-device dataset for urban acoustic scene classification

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