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cs.CL2026
Rethinking Length-Based Training: Batch Composition and Loss Normalization in Speech Token Language Models
Hongjin Song, Runwu Shi, Weiqiao Shan +4
Short-to-long training is a simple curriculum for speech models, but its gains can be difficult to interpret. In speech token language models, length-based training can change the…
cs.CL2022
MT4SSL: Boosting Self-Supervised Speech Representation Learning by Integrating Multiple Targets
Ziyang Ma, Zhisheng Zheng, Changli Tang +2
In this paper, we provide a new perspective on self-supervised speech models from how the training targets are obtained. We generalize the targets extractor into Offline Targets Ex…