7 citations · 7 across the 4 of their papers we have counts for
6 papers
Dialogue State Tracking with a Language Model using Schema-Driven Prompting
Chia-Hsuan Lee, Hao Cheng, Mari Ostendorf
Task-oriented conversational systems often use dialogue state tracking to represent the user's intentions, which involves filling in values of pre-defined slots. Many approaches ha…
KaggleDBQA: Realistic Evaluation of Text-to-SQL Parsers
Chia-Hsuan Lee, Oleksandr Polozov, Matthew Richardson
The goal of database question answering is to enable natural language querying of real-life relational databases in diverse application domains. Recently, large-scale datasets such…
Cross-Lingual Transfer Learning for Question Answering
Chia-Hsuan Lee, Hung-Yi Lee
Deep learning based question answering (QA) on English documents has achieved success because there is a large amount of English training examples. However, for most languages, tra…
Mitigating the Impact of Speech Recognition Errors on Spoken Question Answering by Adversarial Domain Adaptation
Chia-Hsuan Lee, Yun-Nung Chen, Hung-Yi Lee
Spoken question answering (SQA) is challenging due to complex reasoning on top of the spoken documents. The recent studies have also shown the catastrophic impact of automatic spee…
ODSQA: Open-domain Spoken Question Answering Dataset
Chia-Hsuan Lee, Shang-Ming Wang, Huan-Cheng Chang +1
Reading comprehension by machine has been widely studied, but machine comprehension of spoken content is still a less investigated problem. In this paper, we release Open-Domain Sp…
Spoken SQuAD: A Study of Mitigating the Impact of Speech Recognition Errors on Listening Comprehension
Chia-Hsuan Li, Szu-Lin Wu, Chi-Liang Liu +1
Reading comprehension has been widely studied. One of the most representative reading comprehension tasks is Stanford Question Answering Dataset (SQuAD), on which machine is alread…