4 accepted papers
Streaming speech enhancement is a crucial task for real-time applications such as online meetings, smart home appliances, and hearing aids. Deep neural network-based approaches achieve exceptional performance while demanding substantial computational resources. Although recent neural speech enhancem…
The Mobile Object Manipulation Operator (MOMO) is an innovative and reconfigurable robotic system that transforms traditional serving robots into mobile manipulators. Leveraging the form factor and mobility of serving robots, MOMO integrates up to three pluggable devices, including 6-DoF manipulator…
We introduce EM-Network, a novel self-distillation approach that effectively leverages target information for supervised sequence-to-sequence (seq2seq) learning. In contrast to conventional methods, it is trained with oracle guidance, which is derived from the target sequence. Since the oracle guida…
Deep speaker embedding systems are usually trained with classification-based or end-to-end learning objectives. Popular end-to-end approaches utilize deep metric learning, which can be viewed as a few-shot classification objective. In this paper, we investigate the limit of conventional learning obj…