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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
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,…
cs.CL2022
M-Adapter: Modality Adaptation for End-to-End Speech-to-Text Translation
Jinming Zhao, Hao Yang, Ehsan Shareghi +1
End-to-end speech-to-text translation models are often initialized with pre-trained speech encoder and pre-trained text decoder. This leads to a significant training gap between pr…