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CIF-PT: Bridging Speech and Text Representations for Spoken Language Understanding via Continuous Integrate-and-Fire Pre-Training
We also observe the cross-modal representation extracted by CIF-PT obtains better performance than other neural interfaces for the tasks of SLU, including the dominant speech representation learned from self-supervised pre-training.
Improving Contextual Representation with Gloss Regularized Pre-training
To tackle this issue, we propose an auxiliary gloss regularizer module to BERT pre-training (GR-BERT), to enhance word semantic similarity.
Towards Diverse Paraphrase Generation Using Multi-Class Wasserstein GAN
We propose a multi-class extension to the Wasserstein GAN, which allows our generative model to learn from both positive and negative samples.
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