139 citations · 149 across the 6 of their papers we have counts for
7 papers
The NTNU System at the Interspeech 2020 Non-Native Children's Speech ASR Challenge
Tien-Hong Lo, Fu-An Chao, Shi-Yan Weng +1
This paper describes the NTNU ASR system participating in the Interspeech 2020 Non-Native Children's Speech ASR Challenge supported by the SIG-CHILD group of ISCA. This ASR shared…
An Effective Contextual Language Modeling Framework for Speech Summarization with Augmented Features
Shi-Yan Weng, Tien-Hong Lo, Berlin Chen
Tremendous amounts of multimedia associated with speech information are driving an urgent need to develop efficient and effective automatic summarization methods. To this end, we h…
An Effective End-to-End Modeling Approach for Mispronunciation Detection
Tien-Hong Lo, Shi-Yan Weng, Hsiu-Jui Chang +1
Recently, end-to-end (E2E) automatic speech recognition (ASR) systems have garnered tremendous attention because of their great success and unified modeling paradigms in comparison…
An End-to-End Mispronunciation Detection System for L2 English Speech Leveraging Novel Anti-Phone Modeling
Bi-Cheng Yan, Meng-Che Wu, Hsiao-Tsung Hung +1
Mispronunciation detection and diagnosis (MDD) is a core component of computer-assisted pronunciation training (CAPT). Most of the existing MDD approaches focus on dealing with cat…
What do you learn from context? Probing for sentence structure in contextualized word representations
Ian Tenney, Patrick Xia, Berlin Chen +8
Contextualized representation models such as ELMo (Peters et al., 2018a) and BERT (Devlin et al., 2018) have recently achieved state-of-the-art results on a diverse array of downst…
Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling
Alex Wang, Jan Hula, Patrick Xia +13
Natural language understanding has recently seen a surge of progress with the use of sentence encoders like ELMo (Peters et al., 2018a) and BERT (Devlin et al., 2019) which are pre…