Papers with performance-boosting techniques

1 papers
Data Augmentation for Voice-Assistant NLU using BERT-based Interchangeable Rephrase (2021.eacl-main)

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Challenge: a data augmentation technique is used to boost performance on spoken language understanding tasks.
Approach: They propose a data augmentation technique based on byte pair encoding and a BERT-like self-attention model to boost performance on spoken language understanding tasks.
Outcome: The proposed method performs well on domain and intent classification tasks for a voice assistant and in a user-study focused on utterance naturalness and semantic similarity.

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