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Most language understanding models in task-oriented dialog systems are trained on a small amount of annotated training data, and evaluated in a small set from the same distribution.
Switchboard: Telephone speech corpus for research and development
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Robin J Lickley. 1995 · 1995
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Text chunking using transformation-based learning
Lance A Ramshaw and Mitchell P Marcus. 1999 · 1999
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Correction of disfluencies in spontaneous speech using a noisy-channel approach
Matthias Honal and Tanja Schultz. 2003 · 2003
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Textat: Adversarial training for natural language understanding with token-level perturbation
Linyang Li and Xipeng Qiu. 2020 · 2004
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Error simulation for training statistical dialogue systems
Jost Schatzmann, Blaise Thomson, and Steve Young. 2007 · 2007
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Ting Han, Ximing Liu, Ryuichi Takanobu, Yixin Lian, Chongxuan Huang, Wei Peng, and Minlie Huang. 2020 · 2010
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Model-portability experiments for textual temporal analysis
Oleksandr Kolomiyets, Steven Bethard, and Marie-Francine Moens. 2011 · 2011
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Discriminative spoken language understanding using word confusion networks
Matthew Henderson, Milica Gašić, Blaise Thomson, Pirros Tsiakoulis, Kai Yu, and Steve Young. 2012 · 2012
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Targeted feature dropout for robust slot filling in natural language understanding
Puyang Xu and Ruhi Sarikaya. 2014 · 2014
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Deep speech 2: End-to-end speech recognition in english and mandarin
Dario Amodei, Sundaram Ananthanarayanan, Rishita Anubhai, Jingliang Bai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Qiang Cheng, Guoliang Chen, et al. 2016 · 2016
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Incorporating copying mechanism in sequence-to-sequence learning
Jiatao Gu, Zhengdong Lu, Hang Li, and Victor OK Li. 2016 · 2016
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Multi-domain joint semantic frame parsing using bi-directional rnn-lstm
Dilek Hakkani-Tür, Gokhan Tur, Asli Celikyilmaz, Yun-Nung Chen, Jianfeng Gao, Li Deng, and Ye-Yi Wang. 2016 · 2016
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Attention-based recurrent neural network models for joint intent detection and slot filling
Bing Liu and Ian Lane. 2016 · 2016
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Wavenet: A generative model for raw audio
Aaron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior, and Koray Kavukcuoglu. 2016 · 2016
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Crafting adversarial input sequences for recurrent neural networks
Nicolas Papernot, Patrick McDaniel, Ananthram Swami, and Richard Harang. 2016 · 2016
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Disfluency detection using a bidirectional lstm
Vicky Zayats, Mari Ostendorf, and Hannaneh Hajishirzi. 2016 · 2016
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Frames: a corpus for adding memory to goal-oriented dialogue systems
Layla El Asri, Hannes Schulz, Shikhar Kr Sarma, Jeremie Zumer, Justin Harris, Emery Fine, Rahul Mehrotra, and Kaheer Suleman. 2017 · 2017
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Bootstrapping incremental dialogue systems from minimal data: the generalisation power of dialogue grammars
Arash Eshghi, Igor Shalyminov, and Oliver Lemon. 2017 · 2017
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Generating natural language adversarial examples
Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, Bo-Jhang Ho, Mani Srivastava, and Kai-Wei Chang. 2018 · 2018
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Patient and consumer safety risks when using conversational assistants for medical information: an observational study of siri, alexa, and google assistant
Timothy W Bickmore, Ha Trinh, Stefan Olafsson, Teresa K O’Leary, Reza Asadi, Nathaniel M Rickles, and Ricardo Cruz. 2018 · 2018
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Multiwoz-a large-scale multi-domain wizard-of-oz dataset for task-oriented dialogue modelling
Paweł Budzianowski, Tsung-Hsien Wen, Bo-Hsiang Tseng, Iñigo Casanueva, Stefan Ultes, Osman Ramadan, and Milica Gasic. 2018 · 2018
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Hotflip: White-box adversarial examples for text classification
Javid Ebrahimi, Anyi Rao, Daniel Lowd, and Dejing Dou. 2018 · 2018
Textbugger: Generating adversarial text against real-world applications
Jinfeng Li, Shouling Ji, Tianyu Du, Bo Li, and Ting Wang. 2019 · 2019
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Cm-net: A novel collaborative memory network for spoken language understanding
Yijin Liu, Fandong Meng, Jinchao Zhang, Jie Zhou, Yufeng Chen, and Jinan Xu. 2019 · 2019
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Specaugment: A simple data augmentation method for automatic speech recognition
Daniel S Park, William Chan, Yu Zhang, Chung-Cheng Chiu, Barret Zoph, Ekin D Cubuk, and Quoc V Le. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Generating natural language adversarial examples through probability weighted word saliency
Shuhuai Ren, Yihe Deng, Kun He, and Wanxiang Che. 2019 · 2019
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Cited alongside, same era.
Slot-gated modeling for joint slot filling and intent prediction
Chih-Wen Goo, Guang Gao, Yun-Kai Hsu, Chih-Li Huo, Tsung-Chieh Chen, Keng-Wei Hsu, and Yun-Nung Chen. 2018 · 2018
Cited alongside, same era.
Adversarial example generation with syntactically controlled paraphrase networks
Mohit Iyyer, John Wieting, Kevin Gimpel, and Luke Zettlemoyer. 2018 · 2018
Cited alongside, same era.
Data collection for dialogue system: A startup perspective
Yiping Kang, Yunqi Zhang, Jonathan K Kummerfeld, Lingjia Tang, and Jason Mars. 2018 · 2018
Cited alongside, same era.
Disfluency insertion for spontaneous tts: Formalization and proof of concept
Raheel Qader, Gwénolé Lecorvé, Damien Lolive, and Pascale Sébillot. 2018 · 2018
Cited alongside, same era.
Robust spoken language understanding via paraphrasing
Avik Ray, Yilin Shen, and Hongxia Jin. 2018 · 2018
Cited alongside, same era.
A bi-model based rnn semantic frame parsing model for intent detection and slot filling
Yu Wang, Yilin Shen, and Hongxia Jin. 2018 · 2018
Cited alongside, same era.
Improving slot filling in spoken language understanding with joint pointer and attention
Lin Zhao and Zhe Feng. 2018 · 2018
Cited alongside, same era.
Robust zero-shot cross-domain slot filling with example values
Darsh Shah, Raghav Gupta, Amir Fayazi, and Dilek Hakkani-Tur. 2019 · 2019
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Eda: Easy data augmentation techniques for boosting performance on text classification tasks
Jason Wei and Kai Zou. 2019 · 2019
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Data augmentation for spoken language understanding via joint variational generation
Kang Min Yoo, Youhyun Shin, and Sang-goo Lee. 2019 · 2019
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Data augmentation with atomic templates for spoken language understanding
Zijian Zhao, Su Zhu, and Kai Yu. 2019 · 2019
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Effects of naturalistic variation in goal-oriented dialog
Jatin Ganhotra, Robert C Moore, Sachindra Joshi, and Kahini Wadhawan. 2020 · 2020
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Learning to tag oov tokens by integrating contextual representation and background knowledge
Keqing He, Yuanmeng Yan, and XU Weiran. 2020 · 2020
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Is bert really robust? a strong baseline for natural language attack on text classification and entailment
Di Jin, Zhijing Jin, Joey Tianyi Zhou, and Peter Szolovits. 2020 · 2020
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Few-shot natural language generation for task-oriented dialog
Baolin Peng, Chenguang Zhu, Chunyuan Li, Xiujun Li, Jinchao Li, Michael Zeng, and Jianfeng Gao. 2020 · 2020
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Beyond accuracy: Behavioral testing of nlp models with checklist
Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin, and Sameer Singh. 2020 · 2020
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Is your goal-oriented dialog model performing really well? empirical analysis of system-wise evaluation
Ryuichi Takanobu, Qi Zhu, Jinchao Li, Baolin Peng, Jianfeng Gao, and Minlie Huang. 2020 · 2020
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Tod-bert: Pre-trained natural language understanding for task-oriented dialogue
Chien-Sheng Wu, Steven CH Hoi, Richard Socher, and Caiming Xiong. 2020 · 2020
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Convlab-2: An open-source toolkit for building, evaluating, and diagnosing dialogue systems
Qi Zhu, Zheng Zhang, Yan Fang, Xiang Li, Ryuichi Takanobu, Jinchao Li, Baolin Peng, Jianfeng Gao, Xiaoyan Zhu, and Minlie Huang. 2020 · 2020
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