4 citations · 9 across the 4 of their papers we have counts for
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cs.CL2020
Detecting and Exorcising Statistical Demons from Language Models with Anti-Models of Negative Data
Michael L. Wick, Kate Silverstein, Jean-Baptiste Tristan +2
It's been said that "Language Models are Unsupervised Multitask Learners." Indeed, self-supervised language models trained on "positive" examples of English text generalize in desi…
eess.AS2020
End-to-End Speech Recognition and Disfluency Removal
Paria Jamshid Lou, Mark Johnson
Disfluency detection is usually an intermediate step between an automatic speech recognition (ASR) system and a downstream task. By contrast, this paper aims to investigate the tas…
cs.CL2020
Improving Disfluency Detection by Self-Training a Self-Attentive Model
Paria Jamshid Lou, Mark Johnson
Self-attentive neural syntactic parsers using contextualized word embeddings (e.g. ELMo or BERT) currently produce state-of-the-art results in joint parsing and disfluency detectio…