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Found 5 papers, 5 papers with code
Stethoscope-guided Supervised Contrastive Learning for Cross-domain Adaptation on Respiratory Sound Classification
Despite the remarkable advances in deep learning technology, achieving satisfactory performance in lung sound classification remains a challenge due to the scarcity of available data.
Ranked #3 on
Audio Classification
on ICBHI Respiratory Sound Database
(using extra training data)
Adversarial Fine-tuning using Generated Respiratory Sound to Address Class Imbalance
In this work, we propose a straightforward approach to augment imbalanced respiratory sound data using an audio diffusion model as a conditional neural vocoder.
Ranked #2 on
Audio Classification
on ICBHI Respiratory Sound Database
(using extra training data)
Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification
Respiratory sound contains crucial information for the early diagnosis of fatal lung diseases.
Ranked #1 on
Audio Classification
on ICBHI Respiratory Sound Database
(using extra training data)
Vocoder-free End-to-End Voice Conversion with Transformer Network
The additional pre/post processing such as MFB and vocoder is not essential to convert real human speech to others.
End-to-end Multimodal Emotion and Gender Recognition with Dynamic Joint Loss Weights
In our experiments, emotion and gender recognition with the proposed method yielded a lower joint loss, which is computed as the negative log-likelihood, than using static weights for joint loss.
