Acoustic Scene Classification
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Benchmarks
Most implemented
The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification
Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models
Efficient Training of Audio Transformers with Patchout
SELD-TCN: Sound Event Localization & Detection via Temporal Convolutional Networks
Receptive-field-regularized CNN variants for acoustic scene classification
Training neural audio classifiers with few data
Papers
Device Invariance using Domain Adaptation on Acoustic Scene Classification
This paper explores the effectiveness of domain adaptation techniques when using convolutional neural network (CNN)-based and transformer-based feature representations for acoustic scene classification. Two well-known do…
Acoustic Scene ClassificationDomain AdaptationCross-Cultural Bias in Mel-Scale Representations: Evidence and Alternatives from Speech and Music
Modern audio systems universally employ mel-scale representations derived from 1940s Western psychoacoustic studies, potentially encoding cultural biases that create systematic performance disparities. We present a compr…
Acoustic Scene ClassificationSpeech RecognitionFrom Diet to Free Lunch: Estimating Auxiliary Signal Properties using Dynamic Pruning Masks in Speech Enhancement Networks
Speech Enhancement (SE) in audio devices is often supported by auxiliary modules for Voice Activity Detection (VAD), SNR estimation, or Acoustic Scene Classification to ensure robust context-aware behavior and seamless u…
Acoustic Scene ClassificationSpeech EnhancementActivity DetectionDDSC: Dynamic Dual-Signal Curriculum for Data-Efficient Acoustic Scene Classification under Domain Shift
Acoustic scene classification (ASC) suffers from device-induced domain shift, especially when labels are limited. Prior work focuses on curriculum-based training schedules that structure data presentation by ordering or …
Acoustic Scene ClassificationLightweight and Generalizable Acoustic Scene Representations via Contrastive Fine-Tuning and Distillation
Acoustic scene classification (ASC) models on edge devices typically operate under fixed class assumptions, lacking the transferability needed for real-world applications that require adaptation to new or refined acousti…
Acoustic Scene ClassificationAn Entropy-Guided Curriculum Learning Strategy for Data-Efficient Acoustic Scene Classification under Domain Shift
Acoustic Scene Classification (ASC) faces challenges in generalizing across recording devices, particularly when labeled data is limited. The DCASE 2024 Challenge Task 1 highlights this issue by requiring models to learn…
Acoustic Scene ClassificationData Augmentation