156 citations
- Amazon (United States)US12 papers
- Massachusetts Institute of TechnologyUS7 papers
- Carnegie Mellon UniversityUS6 papers
- Google (United States)US5 papers
- Johns Hopkins UniversityUS5 papers
- Meta (Israel)IL5 papers
- California Southern UniversityUS4 papers
- Microsoft Research (United Kingdom)GB4 papers
- Toyota Technological Institute at ChicagoUS4 papers
- University of California, Los AngelesUS4 papers
- University of Southern CaliforniaUS4 papers
- National Yang Ming Chiao Tung UniversityTW3 papers
26 papers · 2 filters
Using multiple ASR hypotheses to boost i18n NLU performance
Charith Peris, Gokmen Oz, Khadige Abboud +3
Current voice assistants typically use the best hypothesis yielded by their Automatic Speech Recognition (ASR) module as input to their Natural Language Understanding (NLU) module,…
Generative Adversarial Networks for Annotated Data Augmentation in Data Sparse NLU
Olga Golovneva, Charith Peris
Data sparsity is one of the key challenges associated with model development in Natural Language Understanding (NLU) for conversational agents. The challenge is made more complex b…
Delexicalized Paraphrase Generation
Boya Yu, Konstantine Arkoudas, Wael Hamza
We present a neural model for paraphrasing and train it to generate delexicalized sentences. We achieve this by creating training data in which each input is paired with a number o…
Dialog Simulation with Realistic Variations for Training Goal-Oriented Conversational Systems
Chien-Wei Lin, Vincent Auvray, Daniel Elkind +10
Goal-oriented dialog systems enable users to complete specific goals like requesting information about a movie or booking a ticket. Typically the dialog system pipeline contains mu…
To What Degree Can Language Borders Be Blurred In BERT-based Multilingual Spoken Language Understanding?
Quynh Do, Judith Gaspers, Tobias Roding +1
This paper addresses the question as to what degree a BERT-based multilingual Spoken Language Understanding (SLU) model can transfer knowledge across languages. Through experiments…
Optimal Subarchitecture Extraction For BERT
Adrian de Wynter, Daniel J. Perry
We extract an optimal subset of architectural parameters for the BERT architecture from Devlin et al. (2018) by applying recent breakthroughs in algorithms for neural architecture…