선별적 상태 공간 모델인 마바를 활용하여 폴리 사운드를 생성하는 모델 MambaFoley를 제안한다.
This paper proposes an efficient backpropagation algorithm and implementation for time-varying all-pole filters that can be used to model various analog audio systems end-to-end using gradient descent.
Non-negative matrix factorization (NMF) can be extended to irregularly-sampled time-frequency representations by formulating it in terms of continuous functions instead of fixed vectors, enabling the use of implicit neural representations to model the underlying basis templates and activations.
Transformers are effective for audio tasks with self-supervised pretraining, enhancing performance across various classification tasks.
Transformers are adapted for audio tasks through self-supervised pretraining, enhancing performance in various classification tasks.