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Acoustic Scene Classification
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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
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Improving Acoustic Scene Classification with City Features
Creating a Good Teacher for Knowledge Distillation in Acoustic Scene Classification
Variational Bayesian Adaptive Learning of Deep Latent Variables for Acoustic Knowledge Transfer
Quantum-Enhanced Transformers for Robust Acoustic Scene Classification in IoT Environments
Improving Acoustic Scene Classification in Low-Resource Conditions
Neurobench: DCASE 2020 Acoustic Scene Classification benchmark on XyloAudio 2
Data Efficient Acoustic Scene Classification using Teacher-Informed Confusing Class Instruction
Audio Enhancement for Computer Audition -- An Iterative Training Paradigm Using Sample Importance
Online Domain-Incremental Learning Approach to Classify Acoustic Scenes in All Locations
Low-Complexity Acoustic Scene Classification Using Parallel Attention-Convolution Network
Data-Efficient Low-Complexity Acoustic Scene Classification in the DCASE 2024 Challenge
Deep Space Separable Distillation for Lightweight Acoustic Scene Classification
A Toolchain for Comprehensive Audio/Video Analysis Using Deep Learning Based Multimodal Approach (A use case of riot or violent context detection)
Description on IEEE ICME 2024 Grand Challenge: Semi-supervised Acoustic Scene Classification under Domain Shift
Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities
Bayesian adaptive learning to latent variables via Variational Bayes and Maximum a Posteriori
AudioLog: LLMs-Powered Long Audio Logging with Hybrid Token-Semantic Contrastive Learning
Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models
Audio Event-Relational Graph Representation Learning for Acoustic Scene Classification
Bringing the Discussion of Minima Sharpness to the Audio Domain: a Filter-Normalised Evaluation for Acoustic Scene Classification
On Frequency-Wise Normalizations for Better Recording Device Generalization in Audio Spectrogram Transformers
Domain Information Control at Inference Time for Acoustic Scene Classification
Acoustic Scene Clustering Using Joint Optimization of Deep Embedding Learning and Clustering Iteration
Low-Complexity Acoustic Scene Classification Using Data Augmentation and Lightweight ResNet
DeCoR: Defy Knowledge Forgetting by Predicting Earlier Audio Codes
Low-complexity deep learning frameworks for acoustic scene classification using teacher-student scheme and multiple spectrograms
Device-Robust Acoustic Scene Classification via Impulse Response Augmentation
Compressing audio CNNs with graph centrality based filter pruning
Unsupervised Improvement of Audio-Text Cross-Modal Representations
Incremental Learning of Acoustic Scenes and Sound Events
Short-Term Memory Convolutions
SpectNet : End-to-End Audio Signal Classification Using Learnable Spectrograms
CochlScene: Acquisition of acoustic scene data using crowdsourcing
Multi-dimensional Edge-based Audio Event Relational Graph Representation Learning for Acoustic Scene Classification
Efficient Similarity-based Passive Filter Pruning for Compressing CNNs
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