Multi-task Learning is Not Enough: Representational Entanglement in Dual-output Second Language Speech Recognition 事件

Multi-task Learning is Not Enough: Representational Entanglement in Dual-output Second Language Speech Recognition arXiv:2606.06065v1 Announce Type: new Abstract: Second-language (L2) speech recognition often requires transcriptions of pronunciations and intended meanings. Multi-task learning (MTL) is a natural approach because it assumes that shared representations benefit both outputs. However, this paper shows that this assumption does not hold across Korean and English. MTL improves meaning