--- title: "Papers of 2019 — page 4" description: "Papers of 2019: 480 papers of the Elamur Research library — what each work is about in our own words, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/papers/2019/page/4/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/2019/page/4/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / 2019 # Papers of 2019 — page 4 480 papers · [all years](https://md.research.elamur.ai/free/en/papers/) [← prev](https://md.research.elamur.ai/free/en/papers/2019/page/3/) [1](https://md.research.elamur.ai/free/en/papers/2019/) [2](https://md.research.elamur.ai/free/en/papers/2019/page/2/) [3](https://md.research.elamur.ai/free/en/papers/2019/page/3/) **4** [5](https://md.research.elamur.ai/free/en/papers/2019/page/5/) [next →](https://md.research.elamur.ai/free/en/papers/2019/page/5/) - [Neural Lemmatization of Multiword Expressions](https://md.research.elamur.ai/free/en/papers/lingbulk-2019-schmitt-neural-lemmatization-multiword-expressions/) — Marine Schmitt, Mathieu Constant · English - [Neural Text Generation with Unlikelihood Training](https://md.research.elamur.ai/free/en/papers/welleck-2019-neural-text-generation-unlikelihood-training/) — Sean Welleck, Ilia Kulikov, Stephen Roller, et al. · arXiv:1908.04319 - [Neural Text Summarization: A Critical Evaluation](https://md.research.elamur.ai/free/en/papers/kryscinski-2019-neural-text-summarization-critical-evaluation/) — Wojciech Kryscinski, Nitish Shirish Keskar, Bryan McCann, et al. · Proceedings of the 2019 Conference on Empirical… - [Next Sentence Prediction helps Implicit Discourse Relation Classification within and across Domains](https://md.research.elamur.ai/free/en/papers/shi-2019-next-sentence-prediction-helps-implicit/) — Wei Shi, Vera Demberg · Proceedings of the 2019 Conference on Empirical… - [NULI at SemEval-2019 Task 6: Transfer Learning for Offensive Language Detection using Bidirectional Transformers](https://md.research.elamur.ai/free/en/papers/liu-2019-nuli-semeval-2019-task-6/) — Ping Liu, Wen Li, Liang Zou · Proceedings of the 13th International Workshop… - [oLMpics -- On what Language Model Pre-training Captures](https://md.research.elamur.ai/free/en/papers/talmor-2019-olmpics-language-model-pre-training/) — Alon Talmor, Yanai Elazar, Yoav Goldberg, et al. · arXiv:1912.13283 - [On Measuring Social Biases in Sentence Encoders](https://md.research.elamur.ai/free/en/papers/may-2019-measuring-social-biases-sentence-encoders/) — Chandler May, Alex Wang, Shikha Bordia, et al. · Proceedings of the 2019 Conference of the North… - [On NMT Search Errors and Model Errors: Cat Got Your Tongue?](https://md.research.elamur.ai/free/en/papers/stahlberg-2019-nmt-search-errors-model-errors/) — Felix Stahlberg, Bill Byrne · Proceedings of the 2019 Conference on Empirical… - [One Model to Learn Both: Zero Pronoun Prediction and Translation](https://md.research.elamur.ai/free/en/papers/wang-2019-one-model-learn-both-zero/) — Longyue Wang, Zhaopeng Tu, Xing Wang, et al. · Proceedings of the 2019 Conference on Empirical… - [Open Sesame: Getting inside BERT's Linguistic Knowledge](https://md.research.elamur.ai/free/en/papers/lin-2019-open-sesame-getting-inside-bert/) — Yongjie Lin, Yi Chern Tan, Robert Frank · Proceedings of the 2019 ACL Workshop… - [OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/moon-2019-opendialkg-explainable-conversational-reasoning-attention/) — Seungwhan Moon, Pararth Shah, Anuj Kumar, et al. · Proceedings of the 57th Annual Meeting of the… - [OpenKiwi: An Open Source Framework for Quality Estimation](https://md.research.elamur.ai/free/en/papers/kepler-2019-openkiwi-open-source-framework-quality/) — Fabio Kepler, Jonay Trénous, Marcos Treviso, et al. · Proceedings of the 57th Annual Meeting of the… - [Optuna: A Next-generation Hyperparameter Optimization Framework](https://md.research.elamur.ai/free/en/papers/akiba-2019-optuna-next-generation-hyperparameter-optimization/) — Takuya Akiba, Shotaro Sano, Toshihiko Yanase, et al. · arXiv:1907.10902 - [Opuscula Ugaritico-Accadico-Hebraica: Relative particles, paʿam, and Amraphel](https://md.research.elamur.ai/free/en/papers/hbo-2019-wikander-opuscula-ugaritico-accadico-hebraica-relative/) — Ola Wikander · Ancient Hebrew - [ParaCrawl: Web-scale parallel corpora for the languages of the EU](https://md.research.elamur.ai/free/en/papers/espla-2019-paracrawl-web-scale-parallel-corpora/) — Miquel Esplà, Mikel Forcada, Gema Ramírez-Sánchez, et al. · Proceedings of Machine Translation Summit XVII… - [Passage Re-ranking with BERT](https://md.research.elamur.ai/free/en/papers/nogueira-2019-passage-re-ranking-bert/) — Rodrigo Nogueira, Kyunghyun Cho · arXiv:1901.04085 - [Patient Knowledge Distillation for BERT Model Compression](https://md.research.elamur.ai/free/en/papers/sun-2019-patient-knowledge-distillation-bert-model/) — Siqi Sun, Yu Cheng, Zhe Gan, et al. · arXiv:1908.09355 - [PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification](https://md.research.elamur.ai/free/en/papers/yang-2019-paws-x-cross-lingual-adversarial/) — Yinfei Yang, Yuan Zhang, Chris Tar, et al. · arXiv:1908.11828 - [PAWS: Paraphrase Adversaries from Word Scrambling](https://md.research.elamur.ai/free/en/papers/zhang-2019-paws-paraphrase-adversaries-word-scrambling/) — Yuan Zhang, Jason Baldridge, Luheng He · Proceedings of the 2019 Conference of the North… - [Pay Less Attention with Lightweight and Dynamic Convolutions](https://md.research.elamur.ai/free/en/papers/wu-2019-pay-less-attention-lightweight-dynamic/) — Felix Wu, Angela Fan, Alexei Baevski, et al. · arXiv:1901.10430 - [PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/zhang-2019-pegasus-pre-training-extracted-gap/) — Jingqing Zhang, Yao Zhao, Mohammad Saleh, et al. · arXiv:1912.08777 - [Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good](https://md.research.elamur.ai/free/en/papers/wang-2019-persuasion-good-personalized-persuasive-dialogue/) — Xuewei Wang, Weiyan Shi, Richard Kim, et al. · Proceedings of the 57th Annual Meeting of the… - [PIQA: Reasoning about Physical Commonsense in Natural Language](https://md.research.elamur.ai/free/en/papers/bisk-2019-piqa-reasoning-about-physical-commonsense/) — Yonatan Bisk, Rowan Zellers, Ronan Le Bras, et al. · arXiv:1911.11641 - [Plug and Play Language Models: A Simple Approach to Controlled Text Generation](https://md.research.elamur.ai/free/en/papers/dathathri-2019-plug-play-language-models-simple/) — Sumanth Dathathri, Andrea Madotto, Janice Lan, et al. · arXiv:1912.02164 - [Pooled Contextualized Embeddings for Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/akbik-2019-pooled-contextualized-embeddings-named-entity/) — Alan Akbik, Tanja Bergmann, Roland Vollgraf · Proceedings of the 2019 Conference of the North… - [Pragmatically Informative Text Generation](https://md.research.elamur.ai/free/en/papers/shen-2019-pragmatically-informative-text-generation/) — Sheng Shen, Daniel Fried, Jacob Andreas, et al. · English - [Pre-Training with Whole Word Masking for Chinese BERT](https://md.research.elamur.ai/free/en/papers/cui-2019-pre-training-whole-word-masking/) — Yiming Cui, Wanxiang Che, Ting Liu, et al. · arXiv:1906.08101 · IEEE/ACM Transactions on… - [Predicate Catenae: A Dependency Grammar Analysis of It-Clefts](https://md.research.elamur.ai/free/en/papers/osborne-2019-predicate-catenae-dependency-grammar-analysis/) — Timothy Osborne · English - [Predicting the Type and Target of Offensive Posts in Social Media](https://md.research.elamur.ai/free/en/papers/zampieri-2019-predicting-type-target-offensive-posts/) — Marcos Zampieri, Shervin Malmasi, Preslav Nakov, et al. · Proceedings of the 2019 Conference of the North… - [Predictive Biases in Natural Language Processing Models: A Conceptual Framework and Overview](https://md.research.elamur.ai/free/en/papers/shah-2019-predictive-biases-natural-language-processing/) — Deven Shah, H. Andrew Schwartz, Dirk Hovy · arXiv:1912.11078 · Association for… - [Prepositions and the Grammaticalization of Ancient Hebrew Bipartite Reciprocal Markers](https://md.research.elamur.ai/free/en/papers/hbo-2019-staps-prepositions-grammaticalization-ancient-hebrew-bipartite/) — Camil Staps · Ancient Hebrew - [Probing Natural Language Inference Models through Semantic Fragments](https://md.research.elamur.ai/free/en/papers/richardson-2019-probing-natural-language-inference-models/) — Kyle Richardson, Hai Hu, Lawrence S. Moss, et al. · arXiv:1909.07521 - [Probing the Need for Visual Context in Multimodal Machine Translation](https://md.research.elamur.ai/free/en/papers/caglayan-2019-probing-need-visual-context-multimodal/) — Ozan Caglayan, Pranava Madhyastha, Lucia Specia, et al. · Proceedings of the 2019 Conference of the North… - [Probing What Different NLP Tasks Teach Machines about Function Word Comprehension](https://md.research.elamur.ai/free/en/papers/kim-2019-probing-what-different-nlp-tasks/) — Najoung Kim, Roma Patel, Adam Poliak, et al. · Proceedings of the Eighth Joint Conference on… - [Problem-oriented Corpus Annotation and the Hebrew Bible](https://md.research.elamur.ai/free/en/papers/hbo-2019-joode-problem-oriented-corpus-annotation-hebrew/) — Johan de Joode · Ancient Hebrew - [Proceedings of the Third Workshop on Universal Dependencies (UDW, SyntaxFest 2019)](https://md.research.elamur.ai/free/en/papers/anon-2019-proceedings-third-workshop-universal-dependencies/) — Research library - [Publicly Available Clinical BERT Embeddings](https://md.research.elamur.ai/free/en/papers/alsentzer-2019-publicly-available-clinical-bert-embeddings/) — Emily Alsentzer, John R. Murphy, Willie Boag, et al. · arXiv:1904.03323 - [PubMedQA: A Dataset for Biomedical Research Question Answering](https://md.research.elamur.ai/free/en/papers/jin-2019-pubmedqa-dataset-biomedical-research-question/) — Qiao Jin, Bhuwan Dhingra, Zhengping Liu, et al. · Proceedings of the 2019 Conference on Empirical… - [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://md.research.elamur.ai/free/en/papers/paszke-2019-pytorch-imperative-style-high-performance/) — Adam Paszke, Sam Gross, Francisco Massa, et al. · arXiv:1912.01703 - [Q-learning pour la résolution des anaphores pronominales en langue arabe (Q-learning for pronominal anaphora resolution in Arabic texts)](https://md.research.elamur.ai/free/en/papers/bouzid-2019-q-learning-pour-la-resolution/) — Saoussen Mathlouthi Bouzid, Chiraz Ben Othmane Zribi · Actes de la Conférence sur le Traitement… - [Quantifying the Carbon Emissions of Machine Learning](https://md.research.elamur.ai/free/en/papers/lacoste-2019-quantifying-carbon-emissions-machine-learning/) — Alexandre Lacoste, Alexandra Luccioni, Victor Schmidt, et al. · arXiv:1910.09700 - [Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning](https://md.research.elamur.ai/free/en/papers/dasigi-2019-quoref-reading-comprehension-dataset-questions/) — Pradeep Dasigi, Nelson F. Liu, Ana Marasovic, et al. · English - [Racial Bias in Hate Speech and Abusive Language Detection Datasets](https://md.research.elamur.ai/free/en/papers/davidson-2019-racial-bias-hate-speech-abusive/) — Thomas Davidson, Debasmita Bhattacharya, Ingmar Weber · Proceedings of the Third Workshop on Abusive… - [Ranking Generated Summaries by Correctness: An Interesting but Challenging Application for Natural Language Inference](https://md.research.elamur.ai/free/en/papers/falke-2019-ranking-generated-summaries-correctness-interesting/) — Tobias Falke, Leonardo F. R. Ribeiro, Prasetya Ajie Utama, et al. · Proceedings of the 57th Annual Meeting of the… - [Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index](https://md.research.elamur.ai/free/en/papers/seo-2019-real-time-open-domain-question/) — Minjoon Seo, Jinhyuk Lee, Tom Kwiatkowski, et al. · Proceedings of the 57th Annual Meeting of the… - [Reasoning Over Paragraph Effects in Situations](https://md.research.elamur.ai/free/en/papers/lin-2019-reasoning-over-paragraph-effects-situations/) — Kevin Lin, Oyvind Tafjord, Peter Clark, et al. · Proceedings of the 2nd Workshop on Machine… - [Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches](https://md.research.elamur.ai/free/en/papers/storks-2019-recent-advances-natural-language-inference/) — Shane Storks, Qiaozi Gao, Joyce Y. Chai · arXiv:1904.01172 - [Recursive LSTM Tree Representation for Arc-Standard Transition-Based Dependency Parsing](https://md.research.elamur.ai/free/en/papers/ud-2019-elkaref-recursive-lstm-tree-representation-arc/) — Mohab Elkaref, Bernd Bohnet · English - [Reducing Transformer Depth on Demand with Structured Dropout](https://md.research.elamur.ai/free/en/papers/fan-2019-reducing-transformer-depth-demand-structured/) — Angela Fan, Edouard Grave, Armand Joulin · arXiv:1909.11556 - [Release Strategies and the Social Impacts of Language Models](https://md.research.elamur.ai/free/en/papers/solaiman-2019-release-strategies-social-impacts-language/) — Irene Solaiman, Miles Brundage, Jack Clark, et al. · arXiv:1908.09203 - [Representation Degeneration Problem in Training Natural Language Generation Models](https://md.research.elamur.ai/free/en/papers/gao-2019-representation-degeneration-problem-training-natural/) — Jun Gao, Di He, Xu Tan, et al. · arXiv:1907.12009 - [Restoring Arabic vowels through omission-tolerant dictionary lookup](https://md.research.elamur.ai/free/en/papers/langstream-2019-neme-restoring-arabic-vowels-through-omission/) — Alexis Amid Neme, Sebastien Paumier · Semitic languages - [Results of the WMT19 Metrics Shared Task: Segment-Level and Strong MT Systems Pose Big Challenges](https://md.research.elamur.ai/free/en/papers/ma-2019-results-wmt19-metrics-shared-task/) — Qingsong Ma, Johnny Wei, Ondřej Bojar, et al. · Proceedings of the Fourth Conference on Machine… - [Rethinking templates: A syntactic analysis of verbal morphology in Emirati Arabic](https://md.research.elamur.ai/free/en/papers/lingbulk-2019-kaabi-rethinking-templates-syntactic-analysis-verbal/) — Meera Al Kaabi, Dimitrios Ntelitheos · Semitic languages - [Revealing the Dark Secrets of BERT](https://md.research.elamur.ai/free/en/papers/kovaleva-2019-revealing-dark-secrets-bert/) — Olga Kovaleva, Alexey Romanov, Anna Rogers, et al. · arXiv:1908.08593 - [Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution](https://md.research.elamur.ai/free/en/papers/barhom-2019-revisiting-joint-modeling-cross-document/) — Shany Barhom, Vered Shwartz, Alon Eirew, et al. · Proceedings of the 57th Annual Meeting of the… - [Rewarding Coreference Resolvers for Being Consistent with World Knowledge](https://md.research.elamur.ai/free/en/papers/aralikatte-2019-rewarding-coreference-resolvers-being-consistent/) — Rahul Aralikatte, Heather Lent, Ana Valeria Gonzalez, et al. · Proceedings of the 2019 Conference on Empirical… - [Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/mccoy-2019-right-wrong-reasons-diagnosing-syntactic/) — R. Thomas McCoy, Ellie Pavlick, Tal Linzen · English - [Robust Neural Machine Translation with Doubly Adversarial Inputs](https://md.research.elamur.ai/free/en/papers/cheng-2019-robust-neural-machine-translation-doubly/) — Yong Cheng, Lu Jiang, Wolfgang Macherey · Proceedings of the 57th Annual Meeting of the… - [S2ORC: The Semantic Scholar Open Research Corpus](https://md.research.elamur.ai/free/en/papers/lo-2019-s2orc-semantic-scholar-open-research/) — Kyle Lo, Lucy Lu Wang, Mark Neumann, et al. · arXiv:1911.02782 - [SciBERT: A Pretrained Language Model for Scientific Text](https://md.research.elamur.ai/free/en/papers/beltagy-2019-scibert-pretrained-language-model-scientific/) — Iz Beltagy, Kyle Lo, Arman Cohan · Proceedings of the 2019 Conference on Empirical… - [SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python](https://md.research.elamur.ai/free/en/papers/virtanen-2019-scipy-1-0-fundamental-algorithms/) — Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, et al. · arXiv:1907.10121 (Nature Methods 17, 261 (2020)) - [ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing](https://md.research.elamur.ai/free/en/papers/neumann-2019-scispacy-fast-robust-models-biomedical/) — Mark Neumann, Daniel King, Iz Beltagy, et al. · Proceedings of the 18th BioNLP Workshop and… - [Selective Attention for Context-aware Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/maruf-2019-selective-attention-context-aware-neural/) — Sameen Maruf, André F. T. Martins, Gholamreza Haffari · Proceedings of the 2019 Conference of the North… - [Semantic mapping of participants in legal discourse](https://md.research.elamur.ai/free/en/papers/hbo-2019-hojgaard-semantic-mapping-participants-legal-discourse/) — Christian Canu Højgaard · Ancient Hebrew - [Semantic Neural Machine Translation Using AMR](https://md.research.elamur.ai/free/en/papers/song-2019-semantic-neural-machine-translation-amr/) — Linfeng Song, Daniel Gildea, Yue Zhang, et al. · Machine translation - [Semantic Noise Matters for Neural Natural Language Generation](https://md.research.elamur.ai/free/en/papers/dusek-2019-semantic-noise-matters-neural-natural/) — Ondřej Dušek, David M. Howcroft, Verena Rieser · Proceedings of the 12th International… - [SemEval-2019 Task 3: EmoContext Contextual Emotion Detection in Text](https://md.research.elamur.ai/free/en/papers/chatterjee-2019-semeval-2019-task-3-emocontext/) — Ankush Chatterjee, Kedhar Nath Narahari, Meghana Joshi, et al. · Proceedings of the 13th International Workshop… - [SemEval-2019 Task 4: Hyperpartisan News Detection](https://md.research.elamur.ai/free/en/papers/kiesel-2019-semeval-2019-task-4-hyperpartisan/) — Johannes Kiesel, Maria Mestre, Rishabh Shukla, et al. · Proceedings of the 13th International Workshop… - [SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter](https://md.research.elamur.ai/free/en/papers/basile-2019-semeval-2019-task-5-multilingual/) — Valerio Basile, Cristina Bosco, Elisabetta Fersini, et al. · Proceedings of the 13th International Workshop… - [SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)](https://md.research.elamur.ai/free/en/papers/zampieri-2019-semeval-2019-task-6-identifying/) — Marcos Zampieri, Shervin Malmasi, Preslav Nakov, et al. · arXiv:1903.08983 - [SemEval-2019 Task 7: RumourEval, Determining Rumour Veracity and Support for Rumours](https://md.research.elamur.ai/free/en/papers/gorrell-2019-semeval-2019-task-7-rumoureval/) — Genevieve Gorrell, Elena Kochkina, Maria Liakata, et al. · Proceedings of the 13th International Workshop… - [Semi-automatic Annotation of Event Structure, Argument Structure, and Opposition Structure to WordNet by Using Event Structure Frame](https://md.research.elamur.ai/free/en/papers/im-2019-semi-automatic-annotation-event-structure/) — Seohyun Im · English - [Sentiment Analysis for Arabic in Social Media Network: A Systematic Mapping Study](https://md.research.elamur.ai/free/en/papers/abo-2019-sentiment-analysis-arabic-social-media/) — Mohamed Elhag M. Abo, Ram Gopal Raj, Atika Qazi, et al. · arXiv:1911.05483 - [SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference](https://md.research.elamur.ai/free/en/papers/schmitt-2019-sherliic-typed-event-focused-lexical/) — Martin Schmitt, Hinrich Schütze · English - [Should a conditional marker arise … The diachronic development of conditional sollte in German](https://md.research.elamur.ai/free/en/papers/breitbarth-2019-i-should-conditional-marker-arise/) — Anne Breitbarth · English - [Similarity of Neural Network Representations Revisited](https://md.research.elamur.ai/free/en/papers/kornblith-2019-similarity-neural-network-representations-revisited/) — Simon Kornblith, Mohammad Norouzi, Honglak Lee, et al. · arXiv:1905.00414 - [Simple BERT Models for Relation Extraction and Semantic Role Labeling](https://md.research.elamur.ai/free/en/papers/shi-2019-simple-bert-models-relation-extraction/) — Peng Shi, Jimmy Lin · arXiv:1904.05255 - [Simple, Scalable Adaptation for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/bapna-2019-simple-scalable-adaptation-neural-machine/) — Ankur Bapna, Orhan Firat · Proceedings of the 2019 Conference on Empirical… - [SocialIQA: Commonsense Reasoning about Social Interactions](https://md.research.elamur.ai/free/en/papers/sap-2019-socialiqa-commonsense-reasoning-about-social/) — Maarten Sap, Hannah Rashkin, Derek Chen, et al. · arXiv:1904.09728 - [Sound Changes in the (Pre-)Masoretic Reading Tradition and the Original Pronunciation of Biblical Aramaic](https://md.research.elamur.ai/free/en/papers/hbo-2019-suchard-sound-changes-pre-masoretic-reading/) — Benjamin D. Suchard · Ancient Hebrew - [SpanBERT: Improving Pre-training by Representing and Predicting Spans](https://md.research.elamur.ai/free/en/papers/joshi-2019-spanbert-improving-pre-training-representing/) — Mandar Joshi, Danqi Chen, Yinhan Liu, et al. · arXiv:1907.10529 - [SParC: Cross-Domain Semantic Parsing in Context](https://md.research.elamur.ai/free/en/papers/yu-2019-sparc-cross-domain-semantic-parsing/) — Tao Yu, Rui Zhang, Michihiro Yasunaga, et al. · Proceedings of the 57th Annual Meeting of the… - [SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition](https://md.research.elamur.ai/free/en/papers/park-2019-specaugment-simple-data-augmentation-method/) — Daniel S. Park, William Chan, Yu Zhang, et al. · arXiv:1904.08779 · Proc. Interspeech 2019… - [Speech act attenuation in the history of English: The case of apologies](https://md.research.elamur.ai/free/en/papers/jucker-2019-speech-act-attenuation-history-english/) — Andreas H. 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