53 citations · 72 across the 11 of their papers we have counts for
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eess.AS2023★ 16 cited
SpeechPrompt v2: Prompt Tuning for Speech Classification Tasks
Kai-Wei Chang, Yu-Kai Wang, Hua Shen +4
Prompt tuning is a technology that tunes a small set of parameters to steer a pre-trained language model (LM) to directly generate the output for downstream tasks. Recently, prompt…
eess.AS2023
Ensemble knowledge distillation of self-supervised speech models
Kuan-Po Huang, Tzu-hsun Feng, Yu-Kuan Fu +5
Distilled self-supervised models have shown competitive performance and efficiency in recent years. However, there is a lack of experience in jointly distilling multiple self-super…