2 citations · 4 across the 6 of their papers we have counts for
6 papers
Compositional Generalization in Spoken Language Understanding
Avik Ray, Yilin Shen, Hongxia Jin
State-of-the-art spoken language understanding (SLU) models have shown tremendous success in benchmark SLU datasets, yet they still fail in many practical scenario due to the lack…
Code-Switched Text Synthesis in Unseen Language Pairs
I-Hung Hsu, Avik Ray, Shubham Garg +2
Existing efforts on text synthesis for code-switching mostly require training on code-switched texts in the target language pairs, limiting the deployment of the models to cases la…
Enhancing the Generalization for Intent Classification and Out-of-Domain Detection in SLU
Yilin Shen, Yen-Chang Hsu, Avik Ray +1
Intent classification is a major task in spoken language understanding (SLU). Since most models are built with pre-collected in-domain (IND) training utterances, their ability to d…
Generating Dialogue Responses from a Semantic Latent Space
Wei-Jen Ko, Avik Ray, Yilin Shen +1
Existing open-domain dialogue generation models are usually trained to mimic the gold response in the training set using cross-entropy loss on the vocabulary. However, a good respo…
Iterative Delexicalization for Improved Spoken Language Understanding
Avik Ray, Yilin Shen, Hongxia Jin
Recurrent neural network (RNN) based joint intent classification and slot tagging models have achieved tremendous success in recent years for building spoken language understanding…
Robust Spoken Language Understanding via Paraphrasing
Avik Ray, Yilin Shen, Hongxia Jin
Learning intents and slot labels from user utterances is a fundamental step in all spoken language understanding (SLU) and dialog systems. State-of-the-art neural network based met…