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Found 6 papers, 3 papers with code
Data-Free Generalized Zero-Shot Learning
Firstly, to recover the virtual features of the base data, we model the CLIP features of base class images as samples from a von Mises-Fisher (vMF) distribution based on the pre-trained classifier.
Semi-supervised Sound Event Detection with Local and Global Consistency Regularization
Then, the local consistency is adopted to encourage the model to leverage local features for frame-level predictions, and the global consistency is applied to force features to align with global prototypes through a specially designed contrastive loss.
Audio Generation with Multiple Conditional Diffusion Model
To address this issue, we propose a novel model that enhances the controllability of existing pre-trained text-to-audio models by incorporating additional conditions including content (timestamp) and style (pitch contour and energy contour) as supplements to the text.
A Hybrid System of Sound Event Detection Transformer and Frame-wise Model for DCASE 2022 Task 4
For the frame-wise model, the ICT-TOSHIBA system of DCASE 2021 Task 4 is used.
Couple Learning for semi-supervised sound event detection
The recently proposed Mean Teacher method, which exploits large-scale unlabeled data in a self-ensembling manner, has achieved state-of-the-art results in several semi-supervised learning benchmarks.
Sound Event Detection Transformer: An Event-based End-to-End Model for Sound Event Detection
A critical issue with the frame-based model is that it pursues the best frame-level prediction rather than the best event-level prediction.
