most citedUnderstanding the Effectiveness of Very Large Language Models on Dialog Evaluation

6 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

eess.AS2023

Tensor decomposition for minimization of E2E SLU model toward on-device processing

Yosuke Kashiwagi, Siddhant Arora, Hayato Futami +6

Spoken Language Understanding (SLU) is a critical speech recognition application and is often deployed on edge devices. Consequently, on-device processing plays a significant role…

cs.CL20231 cited

The Pipeline System of ASR and NLU with MLM-based Data Augmentation toward STOP Low-resource Challenge

Hayato Futami, Jessica Huynh, Siddhant Arora +6

This paper describes our system for the low-resource domain adaptation track (Track 3) in Spoken Language Understanding Grand Challenge, which is a part of ICASSP Signal Processing…

cs.CL20231 cited

A Study on the Integration of Pipeline and E2E SLU systems for Spoken Semantic Parsing toward STOP Quality Challenge

Siddhant Arora, Hayato Futami, Shih-Lun Wu +6

Recently there have been efforts to introduce new benchmark tasks for spoken language understanding (SLU), like semantic parsing. In this paper, we describe our proposed spoken sem…

cs.CL20236 cited

Understanding the Effectiveness of Very Large Language Models on Dialog Evaluation

Jessica Huynh, Cathy Jiao, Prakhar Gupta +4

Language models have steadily increased in size over the past few years. They achieve a high level of performance on various natural language processing (NLP) tasks such as questio…

cs.HC2022

The DialPort tools

Jessica Huynh, Shikib Mehri, Cathy Jiao +1

The DialPort project http://dialport.org/, funded by the National Science Foundation (NSF), covers a group of tools and services that aim at fulfilling the needs of the dialog rese…