University of California, Los Angeles（加州大学洛杉矶分校）

2211.09949 2026-07-23 cs.CL cs.LG cs.SD eess.AS

Is Smaller Always Faster? Tradeoffs in Compressing Self-Supervised Speech Transformers

更小的总是更快的吗？压缩自监督语音Transformer的权衡

Tzu-Quan Lin, Tsung-Huan Yang, Chun-Yao Chang, Kuang-Ming Chen, Tzu-hsun Feng, Hung-yi Lee, Hao Tang

机构 * Graduate Institute of Communication Engineering, National Taiwan University, Taiwan（台湾国立台湾大学通信工程研究所）； University of California, Los Angeles, United States（美国加州大学洛杉矶分校）； University of Washington, United States（美国华盛顿大学）； University of Edinburgh, United Kingdom（英国爱丁堡大学）

AI总结本文研究了压缩自监督语音Transformer的权衡，评估了四种压缩方法并比较了几种最新技术，为实际部署提供指导。

Comments Accepted at ASRU 2025. Code is available at https://github.com/nervjack2/Speech-SSL-Compression

Journal ref 2025 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), pp. 1-7