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Reading comprehension by machine has been widely studied, but machine comprehension of spoken content is still a less investigated problem.
“Subword unit representations for spoken document retrieval,”
Kenney Ng and Victor W Zue, · 1997
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“Using machine learning method and subword unit representations for spoken document categorization,”
Weidong Qu and Katsuhiko Shirai, · 2000
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“Sphinx-4: A flexible open source framework for speech recognition,”
Willie Walker, Paul Lamere, Philip Kwok, Bhiksha Raj, Rita Singh, Evandro Gouvea, Peter Wolf, and Joe Woelfel, · 2004
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“Overview of qast 2008,”
Jordi Turmo, Pere R Comas, Sophie Rosset, Lori Lamel, Nicolas Moreau, and Djamel Mostefa, · 2008
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“Collecting highly parallel data for paraphrase evaluation,”
David L Chen and William B Dolan, · 2011
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“Unsupervised acoustic sub-word unit detection for query-by-example spoken term detection,”
Marijn Huijbregts, Mitchell McLaren, and David Van Leeuwen, · 2011
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“Learning sub-word units for open vocabulary speech recognition,”
Carolina Parada, Mark Dredze, Abhinav Sethy, and Ariya Rastrow, · 2011
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“Factoid question answering for spoken documents,”
Pere R Comas Umbert, · 2012
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“Sibyl, a factoid question-answering system for spoken documents,”
Pere R Comas, Jordi Turmo, and Lluís Màrquez, · 2012
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“Mctest: A challenge dataset for the open-domain machine comprehension of text,”
Matthew Richardson, Christopher JC Burges, and Erin Renshaw, · 2013
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“A thousand frames in just a few words: Lingual description of videos through latent topics and sparse object stitching,”
Pradipto Das, Chenliang Xu, Richard F Doell, and Jason J Corso, · 2013
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“Multi-style adaptive training for robust cross-lingual spoken language understanding,”
Xiaodong He, Li Deng, Dilek Hakkani-Tur, and Gokhan Tur, · 2013
Earlier work this paper cites.
“Spoken question answering using tree-structured conditional random fields and two-layer random walk,”
Sz-Rung Shiang, Hung-yi Lee, and Lin-shan Lee, · 2014
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“From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions,”
Peter Young, Alice Lai, Micah Hodosh, and Julia Hockenmaier, · 2014
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“Microsoft coco: Common objects in context,”
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick, · 2014
Cited alongside, same era.
“What are you talking about? text-to-image coreference,”
Chen Kong, Dahua Lin, Mohit Bansal, Raquel Urtasun, and Sanja Fidler, · 2014
Cited alongside, same era.
“Learning knowledge graphs for question answering through conversational dialog,”
Ben Hixon, Peter Clark, and Hannaneh Hajishirzi, · 2015
Cited alongside, same era.
“A dataset for movie description,”
Anna Rohrbach, Marcus Rohrbach, Niket Tandon, and Bernt Schiele, · 2015
Cited alongside, same era.
“Character-level convolutional networks for text classification,”
Xiang Zhang, Junbo Zhao, and Yann LeCun, · 2015
Cited alongside, same era.
“Squad: 100,000+ questions for machine comprehension of text,”
“Bidirectional attention flow for machine comprehension,”
Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi, · 2016
Later among the works it cites.
“Phoneme embedding and its application to speech driven talking avatar synthesis.,”
Xu Li, Zhiyong Wu, Helen M Meng, Jia Jia, Xiaoyan Lou, and Lianhong Cai, · 2016
Later among the works it cites.
“Supervised and unsupervised transfer learning for question answering,”
Yu-An Chung, Hung-Yi Lee, and James Glass, · 2017
Later among the works it cites.
“Race: Large-scale reading comprehension dataset from examinations,”
Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, and Eduard Hovy, · 2017
Later among the works it cites.
“Constructing sub-word units for spoken term detection,”
Charl van Heerden, Damianos Karakos, Karthik Narasimhan, Marelie Davel, and Richard Schwartz, · 2017
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Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang, · 2016
Cited alongside, same era.
Bo-Hsiang Tseng, Sheng-Syun Shen, Hung-Yi Lee, and Lin-Shan Lee, · 2016
Cited alongside, same era.
“Hierarchical attention model for improved machine comprehension of spoken content,”
Wei Fang, Juei-Yang Hsu, Hung-yi Lee, and Lin-Shan Lee, · 2016
Cited alongside, same era.
“Newsqa: A machine comprehension dataset,”
Adam Trischler, Tong Wang, Xingdi Yuan, Justin Harris, Alessandro Sordoni, Philip Bachman, and Kaheer Suleman, · 2016
Cited alongside, same era.
“Adopting abstract images for semantic scene understanding,”
C Lawrence Zitnick, Ramakrishna Vedantam, and Devi Parikh, · 2016
Cited alongside, same era.
“Movieqa: Understanding stories in movies through question-answering,”
Makarand Tapaswi, Yukun Zhu, Rainer Stiefelhagen, Antonio Torralba, Raquel Urtasun, and Sanja Fidler, · 2016
Cited alongside, same era.
“Character-aware neural language models.,”
Yoon Kim, Yacine Jernite, David Sontag, and Alexander M Rush, · 2016
Cited alongside, same era.
Later among the works it cites.
“Learning to paraphrase for question answering,”
Li Dong, Jonathan Mallinson, Siva Reddy, and Mirella Lapata, · 2017
Later among the works it cites.
“Gated self-matching networks for reading comprehension and question answering,”
Wenhui Wang, Nan Yang, Furu Wei, Baobao Chang, and Ming Zhou, · 2017
Later among the works it cites.
“Fusionnet: Fusing via fully-aware attention with application to machine comprehension,”
Hsin-Yuan Huang, Chenguang Zhu, Yelong Shen, and Weizhu Chen, · 2017
Later among the works it cites.
“Reading wikipedia to answer open-domain questions,”
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes, · 2017
Later among the works it cites.
Chia-Hsuan Li, Szu-Lin Wu, Chi-Liang Liu, and Hung-yi Lee, · 2018
Closest in time.
“Qanet: Combining local convolution with global self-attention for reading comprehension,”
Adams Wei Yu, David Dohan, Minh-Thang Luong, Rui Zhao, Kai Chen, Mohammad Norouzi, and Quoc V Le, · 2018
Closest in time.
“(almost) zero-shot cross-lingual spoken language understanding,”
Shyam Upadhyay, Manaal Faruqui, Gokhan Tur, Dilek Hakkani-Tur, and Larry Heck, · 2018
Closest in time.
“Drcd: a chinese machine reading comprehension dataset,”
Chih Chieh Shao, Trois Liu, Yuting Lai, Yiying Tseng, and Sam Tsai, · 2018
Closest in time.