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Found 5 papers, 0 papers with code
Distributionally Robust Finetuning BERT for Covariate Drift in Spoken Language Understanding
Experiments show that a state-of-the-art BERT-based model suffers performance loss under this drift.
The impact of domain-specific representations on BERT-based multi-domain spoken language understanding
This paper provides the first experimental study on the impact of using domain-specific representations on a BERT-based multi-task spoken language understanding (SLU) model for multi-domain applications.
To What Degree Can Language Borders Be Blurred In BERT-based Multilingual Spoken Language Understanding?
This paper addresses the question as to what degree a BERT-based multilingual Spoken Language Understanding (SLU) model can transfer knowledge across languages.
Data balancing for boosting performance of low-frequency classes in Spoken Language Understanding
Despite the fact that data imbalance is becoming more and more common in real-world Spoken Language Understanding (SLU) applications, it has not been studied extensively in the literature.
Cross-lingual Transfer Learning with Data Selection for Large-Scale Spoken Language Understanding
A typical cross-lingual transfer learning approach boosting model performance on a language is to pre-train the model on all available supervised data from another language.
