Few-Shot Audio Classification
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Benchmarks
BirdClef 2020 (Pruned)
ESC-50
FSDKaggle2018
NSynth
VoxCeleb1
Watkins Marine Mammal Sounds
CREMA-D
Common Voice
Speech Accent Archive
Speech Command v2
Most implemented
Acoustic Prompt Tuning: Empowering Large Language Models with Audition Capabilities
Episodic fine-tuning prototypical networks for optimization-based few-shot learning: Application to audio classification
On the Transferability of Large-Scale Self-Supervision to Few-Shot Audio Classification
MT-SLVR: Multi-Task Self-Supervised Learning for Transformation In(Variant) Representations
MetaAudio: A Few-Shot Audio Classification Benchmark
Papers
SpurAudio: A Benchmark for Studying Shortcut Learning in Few-Shot Audio Classification
Few-shot classification (FSC) is widely used for learning from limited labeled data, yet most evaluations implicitly assume that target concepts are independent of contextual cues. In real-world settings, however, exampl…
Few-Shot Image ClassificationFew-Shot Audio ClassificationPrototypical Contrastive Learning For Improved Few-Shot Audio Classification
Few-shot learning has emerged as a powerful paradigm for training models with limited labeled data, addressing challenges in scenarios where large-scale annotation is impractical. While extensive research has been conduc…
Few-Shot Audio ClassificationContrastive LearningFew-Shot LearningEpisodic fine-tuning prototypical networks for optimization-based few-shot learning: Application to audio classification
The Prototypical Network (ProtoNet) has emerged as a popular choice in Few-shot Learning (FSL) scenarios due to its remarkable performance and straightforward implementation. Building upon such success, we first propose …
Audio ClassificationFew-Shot Audio ClassificationFew-Shot LearningOn the Transferability of Large-Scale Self-Supervision to Few-Shot Audio Classification
In recent years, self-supervised learning has excelled for its capacity to learn robust feature representations from unlabelled data. Networks pretrained through self-supervision serve as effective feature extractors for…
Audio ClassificationFew-Shot Audio ClassificationFew-Shot LearningSelf-Supervised LearningAcoustic Prompt Tuning: Empowering Large Language Models with Audition Capabilities
The auditory system plays a substantial role in shaping the overall human perceptual experience. While prevailing large language models (LLMs) and visual language models (VLMs) have shown their promise in solving a wide …
Audio ClassificationFew-Shot Audio ClassificationLanguage ModelingLanguage Modelling+1MT-SLVR: Multi-Task Self-Supervised Learning for Transformation In(Variant) Representations
Contrastive self-supervised learning has gained attention for its ability to create high-quality representations from large unlabelled data sets. A key reason that these powerful features enable data-efficient learning o…
Few-Shot Audio ClassificationInductive BiasSelf-Supervised LearningUnsupervised Few-Shot Audio Classification