2 papers
eess.AS2024
Hierarchical Recurrent Adapters for Efficient Multi-Task Adaptation of Large Speech Models
Tsendsuren Munkhdalai, Youzheng Chen, Khe Chai Sim +3
Parameter efficient adaptation methods have become a key mechanism to train large pre-trained models for downstream tasks. However, their per-task parameter overhead is considered…
cs.CL2024
Extreme Encoder Output Frame Rate Reduction: Improving Computational Latencies of Large End-to-End Models
Rohit Prabhavalkar, Zhong Meng, Weiran Wang +7
The accuracy of end-to-end (E2E) automatic speech recognition (ASR) models continues to improve as they are scaled to larger sizes, with some now reaching billions of parameters. W…