Scaling few-shot spoken word classification with generative meta-continual learning 事件

Scaling few-shot spoken word classification with generative meta-continual learning arXiv:2605.13075v3 Announce Type: replace Abstract: Few-shot spoken word classification has largely been developed for applications where a small number of classes is considered, and so the potential of larger-scale few-shot spoken word classification remains untapped. This paper investigates the potential of a spoken word classifier to sequentially learn to distinguish between 1000 classes when it is given only