Before revision:  However, the mismatch between training and real-world data causes a shift of speaker embedding space and severely degrades the recognition performance . Various complicated neural architectures are presented to address speaker recognition in the wild but neglect storage and computation requirements. To address this issue , we propose a neural architecture search-based efficient time-delay neural network (EfficientTDNN)  to improve inference efficiency while maintaining recognition accuracy.
After revision:  However, the mismatch between training and real-world data causes a shift of speaker embedding space and severely degrades the recognition performance . Various complicated neural architectures are presented to address speaker recognition in the wild , but these often neglect computation and storage requirements. In this work , we propose a neural architecture search-based efficient time-delay neural network (EfficientTDNN) to improve inference efficiency while maintaining recognition accuracy.