139 citations · 207 across the 14 of their papers we have counts for
6 papers · 1 filter
Cross-utterance Reranking Models with BERT and Graph Convolutional Networks for Conversational Speech Recognition
Shih-Hsuan Chiu, Tien-Hong Lo, Fu-An Chao +1
How to effectively incorporate cross-utterance information cues into a neural language model (LM) has emerged as one of the intriguing issues for automatic speech recognition (ASR)…
Innovative Bert-based Reranking Language Models for Speech Recognition
Shih-Hsuan Chiu, Berlin Chen
More recently, Bidirectional Encoder Representations from Transformers (BERT) was proposed and has achieved impressive success on many natural language processing (NLP) tasks such…
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…
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…
Leveraging Word Embeddings for Spoken Document Summarization
Kuan-Yu Chen, Shih-Hung Liu, Hsin-Min Wang +2
Owing to the rapidly growing multimedia content available on the Internet, extractive spoken document summarization, with the purpose of automatically selecting a set of representa…