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cs.CL2022
Self-supervised Rewiring of Pre-trained Speech Encoders: Towards Faster Fine-tuning with Less Labels in Speech Processing
Hao Yang, Jinming Zhao, Gholamreza Haffari +1
Pre-trained speech Transformers have facilitated great success across various speech processing tasks. However, fine-tuning these encoders for downstream tasks require sufficiently…
cs.CL2022★ 1 cited
Self-supervised Graph Masking Pre-training for Graph-to-Text Generation
Jiuzhou Han, Ehsan Shareghi
Large-scale pre-trained language models (PLMs) have advanced Graph-to-Text (G2T) generation by processing the linearised version of a graph. However, the linearisation is known to…
cs.CL2022
RedApt: An Adaptor for wav2vec 2 Encoding \\ Faster and Smaller Speech Translation without Quality Compromise
Jinming Zhao, Hao Yang, Gholamreza Haffari +1
Pre-trained speech Transformers in speech translation (ST) have facilitated state-of-the-art (SotA) results; yet, using such encoders is computationally expensive. To improve this,…