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ORCIDDaniel Jurafsky
Dan Jurafsky
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- affiliation: Stanford University, USA
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2020 – today
- 2024
[j31]Eva Portelance
, Michael C. Frank, Dan Jurafsky:
Learning the Meanings of Function Words From Grounded Language Using a Visual Question Answering Model. Cogn. Sci. 48(5) (2024)- [j30]Valentin Hofmann, Pratyusha Ria Kalluri, Dan Jurafsky, Sharese King:
AI generates covertly racist decisions about people based on their dialect. Nat. 633(8028): 147-154 (2024) - [j29]Daniel A. McFarland, David Broska, Vinodkumar Prabhakaran, Dan Jurafsky:
Coming into relations: How communication reveals and persuades relational decisions. Soc. Networks 79: 57-75 (2024) - [c205]Aryaman Arora, Dan Jurafsky, Christopher Potts:
CausalGym: Benchmarking causal interpretability methods on linguistic tasks. ACL (1) 2024: 14638-14663 - [c204]Myra Cheng, Kristina Gligoric, Tiziano Piccardi, Dan Jurafsky:
AnthroScore: A Computational Linguistic Measure of Anthropomorphism. EACL (1) 2024: 807-825 - [c203]Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Röttger, Dan Jurafsky, Tatsunori Hashimoto, James Zou:
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions. ICLR 2024 - [c202]Garrett Tanzer, Mirac Suzgun, Eline Visser, Dan Jurafsky, Luke Melas-Kyriazi:
A Benchmark for Learning to Translate a New Language from One Grammar Book. ICLR 2024 - [c201]Federico Bianchi, Patrick John Chia, Mert Yüksekgönül, Jacopo Tagliabue, Dan Jurafsky, James Zou:
How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis. ICML 2024 - [c200]Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff, Dan Jurafsky, Douwe Kiela:
Model Alignment as Prospect Theoretic Optimization. ICML 2024 - [c199]Yiwei Luo, Kristina Gligoric, Dan Jurafsky:
Othering and Low Status Framing of Immigrant Cuisines in US Restaurant Reviews and Large Language Models. ICWSM 2024: 985-998 - [c198]Kristina Gligoric, Myra Cheng, Lucia Zheng, Esin Durmus, Dan Jurafsky:
NLP Systems That Can't Tell Use from Mention Censor Counterspeech, but Teaching the Distinction Helps. NAACL-HLT 2024: 5942-5959 - [c197]Omar Shaikh, Kristina Gligoric, Ashna Khetan, Matthias Gerstgrasser, Diyi Yang, Dan Jurafsky:
Grounding Gaps in Language Model Generations. NAACL-HLT 2024: 6279-6296 - [c196]Nay San, Georgios Paraskevopoulos, Aryaman Arora, Xiluo He, Prabhjot Kaur, Oliver Adams, Dan Jurafsky:
Predicting positive transfer for improved low-resource speech recognition using acoustic pseudo-tokens. SIGTYPE 2024: 100-112 - [i107]Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff, Dan Jurafsky, Douwe Kiela:
KTO: Model Alignment as Prospect Theoretic Optimization. CoRR abs/2402.01306 (2024) - [i106]Myra Cheng, Kristina Gligoric, Tiziano Piccardi, Dan Jurafsky:
AnthroScore: A Computational Linguistic Measure of Anthropomorphism. CoRR abs/2402.02056 (2024) - [i105]Nay San, Georgios Paraskevopoulos, Aryaman Arora, Xiluo He, Prabhjot Kaur, Oliver Adams, Dan Jurafsky:
Predicting positive transfer for improved low-resource speech recognition using acoustic pseudo-tokens. CoRR abs/2402.02302 (2024) - [i104]Federico Bianchi, Patrick John Chia, Mert Yüksekgönül, Jacopo Tagliabue, Dan Jurafsky, James Zou:
How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis. CoRR abs/2402.05863 (2024) - [i103]Aryaman Arora, Dan Jurafsky, Christopher Potts:
CausalGym: Benchmarking causal interpretability methods on linguistic tasks. CoRR abs/2402.12560 (2024) - [i102]Valentin Hofmann, Pratyusha Ria Kalluri, Dan Jurafsky, Sharese King:
Dialect prejudice predicts AI decisions about people's character, employability, and criminality. CoRR abs/2403.00742 (2024) - [i101]Kristina Gligoric, Myra Cheng, Lucia Zheng, Esin Durmus, Dan Jurafsky:
NLP Systems That Can't Tell Use from Mention Censor Counterspeech, but Teaching the Distinction Helps. CoRR abs/2404.01651 (2024) - [i100]Zhengxuan Wu, Aryaman Arora, Zheng Wang, Atticus Geiger, Dan Jurafsky, Christopher D. Manning, Christopher Potts:
ReFT: Representation Finetuning for Language Models. CoRR abs/2404.03592 (2024) - [i99]Jiatong Shi, Shih-Heng Wang, William Chen, Martijn Bartelds, Vanya Bannihatti Kumar, Jinchuan Tian, Xuankai Chang, Dan Jurafsky, Karen Livescu, Hung-yi Lee, Shinji Watanabe:
ML-SUPERB 2.0: Benchmarking Multilingual Speech Models Across Modeling Constraints, Languages, and Datasets. CoRR abs/2406.08641 (2024) - [i98]Kaitlyn Zhou, Jena D. Hwang, Xiang Ren, Nouha Dziri, Dan Jurafsky, Maarten Sap:
Rel-A.I.: An Interaction-Centered Approach To Measuring Human-LM Reliance. CoRR abs/2407.07950 (2024) - [i97]Heidi C. Zhang, Shabnam Behzad, Kawin Ethayarajh, Dan Jurafsky:
Data Checklist: On Unit-Testing Datasets with Usable Information. CoRR abs/2408.02919 (2024) - [i96]Moussa Koulako Bala Doumbouya, Ananjan Nandi, Gabriel Poesia, Davide Ghilardi, Anna Goldie, Federico Bianchi, Dan Jurafsky, Christopher D. Manning:
h4rm3l: A Dynamic Benchmark of Composable Jailbreak Attacks for LLM Safety Assessment. CoRR abs/2408.04811 (2024) - [i95]Antón de la Fuente, Dan Jurafsky:
A layer-wise analysis of Mandarin and English suprasegmentals in SSL speech models. CoRR abs/2408.13678 (2024) - [i94]Kristina Gligoric, Tijana Zrnic, Cinoo Lee, Emmanuel J. Candès, Dan Jurafsky:
Can Unconfident LLM Annotations Be Used for Confident Conclusions? CoRR abs/2408.15204 (2024) - 2023
- [j28]Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley, Percy Liang:
Foundation Models and Fair Use. J. Mach. Learn. Res. 24: 400:1-400:79 (2023) - [c195]Martijn Bartelds, Nay San, Bradley McDonnell, Dan Jurafsky, Martijn Wieling:
Making More of Little Data: Improving Low-Resource Automatic Speech Recognition Using Data Augmentation. ACL (1) 2023: 715-729 - [c194]Myra Cheng, Esin Durmus, Dan Jurafsky:
Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language Models. ACL (1) 2023: 1504-1532 - [c193]Mirac Suzgun, Luke Melas-Kyriazi, Dan Jurafsky:
Follow the Wisdom of the Crowd: Effective Text Generation via Minimum Bayes Risk Decoding. ACL (Findings) 2023: 4265-4293 - [c192]Peter Henderson, Eric Mitchell, Christopher D. Manning, Dan Jurafsky, Chelsea Finn:
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models. AIES 2023: 287-296 - [c191]Isabel Papadimitriou, Kezia Lopez, Dan Jurafsky:
Multilingual BERT has an accent: Evaluating English influences on fluency in multilingual models. EACL (Findings) 2023: 1164-1170 - [c190]Tolúlopé Ògúnrèmí, Dan Jurafsky, Christopher D. Manning:
Mini But Mighty: Efficient Multilingual Pretraining with Linguistically-Informed Data Selection. EACL (Findings) 2023: 1221-1236 - [c189]Faisal Ladhak, Esin Durmus, Mirac Suzgun, Tianyi Zhang, Dan Jurafsky, Kathleen R. McKeown, Tatsunori Hashimoto:
When Do Pre-Training Biases Propagate to Downstream Tasks? A Case Study in Text Summarization. EACL 2023: 3198-3211 - [c188]Kaitlyn Zhou, Dan Jurafsky, Tatsunori Hashimoto:
Navigating the Grey Area: How Expressions of Uncertainty and Overconfidence Affect Language Models. EMNLP 2023: 5506-5524 - [c187]Isabel Papadimitriou, Dan Jurafsky:
Injecting structural hints: Using language models to study inductive biases in language learning. EMNLP (Findings) 2023: 8402-8413 - [c186]Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, Aylin Caliskan:
Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale. FAccT 2023: 1493-1504 - [c185]Mert Yüksekgönül, Federico Bianchi, Pratyusha Kalluri, Dan Jurafsky, James Zou:
When and Why Vision-Language Models Behave like Bags-Of-Words, and What to Do About It? ICLR 2023 - [c184]Anjalie Field, Prateek Verma, Nay San, Jennifer L. Eberhardt, Dan Jurafsky:
Developing Speech Processing Pipelines for Police Accountability. INTERSPEECH 2023: 1229-1233 - [c183]Connor Toups, Rishi Bommasani, Kathleen Creel, Sarah H. Bana, Dan Jurafsky, Percy Liang:
Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes. NeurIPS 2023 - [i93]Nay San, Martijn Bartelds, Blaine Billings, Ella de Falco, Hendi Feriza, Johan Safri, Wawan Sahrozi, Ben Foley, Bradley McDonnell, Dan Jurafsky:
Leveraging supplementary text data to kick-start automatic speech recognition system development with limited transcriptions. CoRR abs/2302.04975 (2023) - [i92]Kaitlyn Zhou, Dan Jurafsky, Tatsunori Hashimoto:
Navigating the Grey Area: Expressions of Overconfidence and Uncertainty in Language Models. CoRR abs/2302.13439 (2023) - [i91]Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley, Percy Liang:
Foundation Models and Fair Use. CoRR abs/2303.15715 (2023) - [i90]Isabel Papadimitriou, Dan Jurafsky:
Pretrain on just structure: Understanding linguistic inductive biases using transfer learning. CoRR abs/2304.13060 (2023) - [i89]Mirac Suzgun, Stuart M. Shieber, Dan Jurafsky:
string2string: A Modern Python Library for String-to-String Algorithms. CoRR abs/2304.14395 (2023) - [i88]Martijn Bartelds, Nay San, Bradley McDonnell, Dan Jurafsky, Martijn Wieling:
Making More of Little Data: Improving Low-Resource Automatic Speech Recognition Using Data Augmentation. CoRR abs/2305.10951 (2023) - [i87]Myra Cheng, Esin Durmus, Dan Jurafsky:
Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language Models. CoRR abs/2305.18189 (2023) - [i86]Anjalie Field, Prateek Verma, Nay San, Jennifer L. Eberhardt, Dan Jurafsky:
Developing Speech Processing Pipelines for Police Accountability. CoRR abs/2306.06086 (2023) - [i85]Connor Toups, Rishi Bommasani, Kathleen A. Creel, Sarah H. Bana, Dan Jurafsky, Percy Liang:
Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes. CoRR abs/2307.05862 (2023) - [i84]Yiwei Luo, Kristina Gligoric, Dan Jurafsky:
Othering and low prestige framing of immigrant cuisines in US restaurant reviews and large language models. CoRR abs/2307.07645 (2023) - [i83]Eva Portelance, Michael C. Frank, Dan Jurafsky:
Learning the meanings of function words from grounded language using a visual question answering model. CoRR abs/2308.08628 (2023) - [i82]Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Röttger, Dan Jurafsky, Tatsunori Hashimoto, James Zou:
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions. CoRR abs/2309.07875 (2023) - [i81]Garrett Tanzer, Mirac Suzgun, Eline Visser, Dan Jurafsky, Luke Melas-Kyriazi:
A Benchmark for Learning to Translate a New Language from One Grammar Book. CoRR abs/2309.16575 (2023) - [i80]Omar Shaikh, Kristina Gligoric, Ashna Khetan, Matthias Gerstgrasser, Diyi Yang, Dan Jurafsky:
Grounding or Guesswork? Large Language Models are Presumptive Grounders. CoRR abs/2311.09144 (2023) - [i79]Tolúlopé Ògúnrèmí, Christopher D. Manning, Dan Jurafsky:
Multilingual self-supervised speech representations improve the speech recognition of low-resource African languages with codeswitching. CoRR abs/2311.15077 (2023) - [i78]Emma Pierson, Divya Shanmugam, Rajiv Movva, Jon M. Kleinberg, Monica Agrawal, Mark Dredze, Kadija Ferryman, Judy Wawira Gichoya, Dan Jurafsky, Pang Wei Koh, Karen Levy, Sendhil Mullainathan, Ziad Obermeyer, Harini Suresh, Keyon Vafa:
Use large language models to promote equity. CoRR abs/2312.14804 (2023) - 2022
- [c182]Kaitlyn Zhou, Kawin Ethayarajh, Dallas Card, Dan Jurafsky:
Problems with Cosine as a Measure of Embedding Similarity for High Frequency Words. ACL (2) 2022: 401-423 - [c181]Kaitlyn Zhou, Kawin Ethayarajh, Dan Jurafsky:
Richer Countries and Richer Representations. ACL (Findings) 2022: 2074-2085 - [c180]Junshen K. Chen, Dallas Card, Dan Jurafsky:
Modular Domain Adaptation. ACL (Findings) 2022: 3633-3655 - [c179]Mirac Suzgun, Luke Melas-Kyriazi, Dan Jurafsky:
Prompt-and-Rerank: A Method for Zero-Shot and Few-Shot Arbitrary Textual Style Transfer with Small Language Models. EMNLP 2022: 2195-2222 - [c178]Kawin Ethayarajh, Dan Jurafsky:
The Authenticity Gap in Human Evaluation. EMNLP 2022: 6056-6070 - [c177]Peter Henderson, Mark S. Krass, Lucia Zheng, Neel Guha, Christopher D. Manning, Dan Jurafsky, Daniel E. Ho:
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. NeurIPS 2022 - [c176]Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang:
Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? NeurIPS 2022 - [i77]Nay San, Martijn Bartelds, Tolúlopé Ògúnrèmí, Alison Mount, Ruben Thompson, Michael Higgins, Roy Barker, Jane Simpson, Dan Jurafsky:
Automated speech tools for helping communities process restricted-access corpora for language revival efforts. CoRR abs/2204.07272 (2022) - [i76]Junshen K. Chen, Dallas Card, Dan Jurafsky:
Modular Domain Adaptation. CoRR abs/2204.14213 (2022) - [i75]Kaitlyn Zhou, Kawin Ethayarajh, Dallas Card, Dan Jurafsky:
Problems with Cosine as a Measure of Embedding Similarity for High Frequency Words. CoRR abs/2205.05092 (2022) - [i74]Kaitlyn Zhou, Kawin Ethayarajh, Dan Jurafsky:
Richer Countries and Richer Representations. CoRR abs/2205.05093 (2022) - [i73]Mirac Suzgun, Luke Melas-Kyriazi, Dan Jurafsky:
Prompt-and-Rerank: A Method for Zero-Shot and Few-Shot Arbitrary Textual Style Transfer with Small Language Models. CoRR abs/2205.11503 (2022) - [i72]Kawin Ethayarajh, Dan Jurafsky:
How Human is Human Evaluation? Improving the Gold Standard for NLG with Utility Theory. CoRR abs/2205.11930 (2022) - [i71]Peter Henderson, Mark S. Krass, Lucia Zheng, Neel Guha, Christopher D. Manning, Dan Jurafsky, Daniel E. Ho:
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. CoRR abs/2207.00220 (2022) - [i70]Sterling Alic, Dorottya Demszky, Zid Mancenido, Jing Liu, Heather Hill, Dan Jurafsky:
Computationally Identifying Funneling and Focusing Questions in Classroom Discourse. CoRR abs/2208.04715 (2022) - [i69]Mert Yüksekgönül, Federico Bianchi, Pratyusha Kalluri, Dan Jurafsky, James Zou:
When and why vision-language models behave like bags-of-words, and what to do about it? CoRR abs/2210.01936 (2022) - [i68]Isabel Papadimitriou, Kezia Lopez, Dan Jurafsky:
Multilingual BERT has an accent: Evaluating English influences on fluency in multilingual models. CoRR abs/2210.05619 (2022) - [i67]Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, Aylin Caliskan:
Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale. CoRR abs/2211.03759 (2022) - [i66]Mirac Suzgun, Luke Melas-Kyriazi, Dan Jurafsky:
Follow the Wisdom of the Crowd: Effective Text Generation via Minimum Bayes Risk Decoding. CoRR abs/2211.07634 (2022) - [i65]Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang:
Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? CoRR abs/2211.13972 (2022) - [i64]Eric Mitchell, Peter Henderson, Christopher D. Manning, Dan Jurafsky, Chelsea Finn:
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses in Foundation Models. CoRR abs/2211.14946 (2022) - 2021
- [j27]Michael Hahn, Dan Jurafsky, Richard Futrell:
Sensitivity as a Complexity Measure for Sequence Classification Tasks. Trans. Assoc. Comput. Linguistics 9: 891-908 (2021) - [c175]Kawin Ethayarajh, Dan Jurafsky:
Attention Flows are Shapley Value Explanations. ACL/IJCNLP (2) 2021: 49-54 - [c174]Dorottya Demszky, Jing Liu, Zid Mancenido, Julie Cohen, Heather Hill, Dan Jurafsky, Tatsunori Hashimoto:
Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions. ACL/IJCNLP (1) 2021: 1638-1653 - [c173]Nay San, Martijn Bartelds, Mitchell Browne, Lily Clifford, Fiona Gibson, John Mansfield, David Nash, Jane Simpson, Myfany Turpin, Maria Vollmer, Sasha Wilmoth, Dan Jurafsky:
Leveraging Pre-Trained Representations to Improve Access to Untranscribed Speech from Endangered Languages. ASRU 2021: 1094-1101 - [c172]Matthew Louis Mauriello, Thierry Lincoln, Grace Hon, Dorien Simon, Dan Jurafsky, Pablo Paredes:
SAD: A Stress Annotated Dataset for Recognizing Everyday Stressors in SMS-like Conversational Systems. CHI Extended Abstracts 2021: 399:1-399:7 - [c171]Eva Portelance, Michael C. Frank, Dan Jurafsky, Alessandro Sordoni, Romain Laroche:
The Emergence of the Shape Bias Results from Communicative Efficiency. CoNLL 2021: 607-623 - [c170]William Held, Dan Iter, Dan Jurafsky:
Focus on what matters: Applying Discourse Coherence Theory to Cross Document Coreference. EMNLP (1) 2021: 1406-1417 - [c169]Urvashi Khandelwal, Angela Fan, Dan Jurafsky, Luke Zettlemoyer, Mike Lewis:
Nearest Neighbor Machine Translation. ICLR 2021 - [c168]Reid Pryzant, Dallas Card, Dan Jurafsky, Victor Veitch, Dhanya Sridhar:
Causal Effects of Linguistic Properties. NAACL-HLT 2021: 4095-4109 - [c167]Yasuhide Miura, Yuhao Zhang, Emily Bao Tsai, Curtis P. Langlotz, Dan Jurafsky:
Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation. NAACL-HLT 2021: 5288-5304 - [i63]Nay San, Martijn Bartelds, Mitchell Browne, Lily Clifford, Fiona Gibson, John Mansfield, David Nash, Jane Simpson, Myfany Turpin, Maria Vollmer, Sasha Wilmoth, Dan Jurafsky:
Leveraging neural representations for facilitating access to untranscribed speech from endangered languages. CoRR abs/2103.14583 (2021) - [i62]Kaitlyn Zhou, Kawin Ethayarajh, Dan Jurafsky:
Frequency-based Distortions in Contextualized Word Embeddings. CoRR abs/2104.08465 (2021) - [i61]Michael Hahn, Dan Jurafsky, Richard Futrell:
Sensitivity as a Complexity Measure for Sequence Classification Tasks. CoRR abs/2104.10343 (2021) - [i60]Kawin Ethayarajh, Dan Jurafsky:
Attention Flows are Shapley Value Explanations. CoRR abs/2105.14652 (2021) - [i59]Dorottya Demszky, Jing Liu, Zid Mancenido, Julie Cohen, Heather Hill, Dan Jurafsky, Tatsunori Hashimoto:
Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions. CoRR abs/2106.03873 (2021) - [i58]Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.:
On the Opportunities and Risks of Foundation Models. CoRR abs/2108.07258 (2021) - [i57]Eva Portelance, Michael C. Frank, Dan Jurafsky, Alessandro Sordoni, Romain Laroche:
The Emergence of the Shape Bias Results from Communicative Efficiency. CoRR abs/2109.06232 (2021) - [i56]William Held, Dan Iter, Dan Jurafsky:
Focus on what matters: Applying Discourse Coherence Theory to Cross Document Coreference. CoRR abs/2110.05362 (2021) - 2020
- [j26]Julia Mendelsohn, Yulia Tsvetkov, Dan Jurafsky:
A Framework for the Computational Linguistic Analysis of Dehumanization. Frontiers Artif. Intell. 3: 55 (2020) - [j25]Adam S. Miner, Albert Haque, Jason A. Fries, Scott L. Fleming, Denise E. Wilfley, G. Terence Wilson, Arnold Milstein, Dan Jurafsky, Bruce A. Arnow, W. Stewart Agras, Li Fei-Fei, Nigam H. Shah:
Assessing the accuracy of automatic speech recognition for psychotherapy. npj Digit. Medicine 3 (2020) - [j24]Allison Koenecke, Andrew Nam, Emily Lake, Joe Nudell, Minnie Quartey, Zion Mengesha, Connor Toups, John R. Rickford, Dan Jurafsky, Sharad Goel:
Racial disparities in automated speech recognition. Proc. Natl. Acad. Sci. USA 117(14): 7684-7689 (2020) - [c166]Reid Pryzant, Richard Diehl Martinez, Nathan Dass, Sadao Kurohashi, Dan Jurafsky, Diyi Yang:
Automatically Neutralizing Subjective Bias in Text. AAAI 2020: 480-489 - [c165]Dan Iter, Kelvin Guu, Larry Lansing, Dan Jurafsky:
Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models. ACL 2020: 4859-4870 - [c164]Maarten Sap, Saadia Gabriel, Lianhui Qin, Dan Jurafsky, Noah A. Smith, Yejin Choi:
Social Bias Frames: Reasoning about Social and Power Implications of Language. ACL 2020: 5477-5490 - [c163]Yiwei Luo, Dallas Card, Dan Jurafsky:
DeSMOG: Detecting Stance in Media On Global Warming. EMNLP (Findings) 2020: 3296-3315 - [c162]Kawin Ethayarajh, Dan Jurafsky:
Utility is in the Eye of the User: A Critique of NLP Leaderboards. EMNLP (1) 2020: 4846-4853 - [c161]Isabel Papadimitriou, Dan Jurafsky:
Learning Music Helps You Read: Using Transfer to Study Linguistic Structure in Language Models. EMNLP (1) 2020: 6829-6839 - [c160]Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, Dan Jurafsky:
With Little Power Comes Great Responsibility. EMNLP (1) 2020: 9263-9274 - [c159]Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, Mike Lewis:
Generalization through Memorization: Nearest Neighbor Language Models. ICLR 2020 - [c158]Alex Tamkin, Dan Jurafsky, Noah D. Goodman:
Language Through a Prism: A Spectral Approach for Multiscale Language Representations. NeurIPS 2020 - [e4]Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel R. Tetreault:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5-10, 2020. Association for Computational Linguistics 2020, ISBN 978-1-952148-25-5 [contents] - [i55]Peter Henderson, Jieru Hu, Joshua Romoff, Emma Brunskill, Dan Jurafsky, Joelle Pineau:
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning. CoRR abs/2002.05651 (2020) - [i54]Julia Mendelsohn, Yulia Tsvetkov, Dan Jurafsky:
A Framework for the Computational Linguistic Analysis of Dehumanization. CoRR abs/2003.03014 (2020) - [i53]Isabel Papadimitriou, Dan Jurafsky:
Pretraining on Non-linguistic Structure as a Tool for Analyzing Learning Bias in Language Models. CoRR abs/2004.14601 (2020) - [i52]Dan Iter, Kelvin Guu, Larry Lansing, Dan Jurafsky:
Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models. CoRR abs/2005.10389 (2020) - [i51]Dorottya Demszky, László Kálmán, Dan Jurafsky, Beth Levin:
The Role of Verb Semantics in Hungarian Verb-Object Order. CoRR abs/2006.09432 (2020) - [i50]Kawin Ethayarajh, Dan Jurafsky:
Utility is in the Eye of the User: A Critique of NLP Leaderboards. CoRR abs/2009.13888 (2020) - [i49]Urvashi Khandelwal, Angela Fan, Dan Jurafsky, Luke Zettlemoyer, Mike Lewis:
Nearest Neighbor Machine Translation. CoRR abs/2010.00710 (2020) - [i48]Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, Dan Jurafsky:
With Little Power Comes Great Responsibility. CoRR abs/2010.06595 (2020) - [i47]Yasuhide Miura, Yuhao Zhang, Curtis P. Langlotz, Dan Jurafsky:
Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation. CoRR abs/2010.10042 (2020) - [i46]Reid Pryzant, Dallas Card, Dan Jurafsky, Victor Veitch, Dhanya Sridhar:
Causal Effects of Linguistic Properties. CoRR abs/2010.12919 (2020) - [i45]Yiwei Luo, Dallas Card, Dan Jurafsky:
DeSMOG: Detecting Stance in Media On Global Warming. CoRR abs/2010.15149 (2020) - [i44]Alex Tamkin, Dan Jurafsky, Noah D. Goodman:
Language Through a Prism: A Spectral Approach for Multiscale Language Representations. CoRR abs/2011.04823 (2020)
2010 – 2019
- 2019
- [c157]Yiwei Luo, Dan Jurafsky, Beth Levin:
From Insanely Jealous to Insanely Delicious: Computational Models for the Semantic Bleaching of English Intensifiers. LChange@ACL 2019: 1-13 - [c156]Diyi Yang, Robert E. Kraut, Tenbroeck Smith, Elijah Mayfield, Dan Jurafsky:
Seekers, Providers, Welcomers, and Storytellers: Modeling Social Roles in Online Health Communities. CHI 2019: 344 - [c155]Julia Kruk, Jonah Lubin, Karan Sikka, Xiao Lin, Dan Jurafsky, Ajay Divakaran:
Integrating Text and Image: Determining Multimodal Document Intent in Instagram Posts. EMNLP/IJCNLP (1) 2019: 4621-4631 - [c154]Dorottya Demszky, Nikhil Garg, Rob Voigt, James Zou, Jesse Shapiro, Matthew Gentzkow, Dan Jurafsky:
Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootings. NAACL-HLT (1) 2019: 2970-3005 - [c153]Diyi Yang, Jiaao Chen, Zichao Yang, Dan Jurafsky, Eduard H. Hovy:
Let's Make Your Request More Persuasive: Modeling Persuasive Strategies via Semi-Supervised Neural Nets on Crowdfunding Platforms. NAACL-HLT (1) 2019: 3620-3630 - [c152]Ignacio Cases, Clemens Rosenbaum, Matthew Riemer, Atticus Geiger, Tim Klinger, Alex Tamkin, Olivia Li, Sandhini Agarwal, Joshua D. Greene, Dan Jurafsky, Christopher Potts, Lauri Karttunen:
Recursive Routing Networks: Learning to Compose Modules for Language Understanding. NAACL-HLT (1) 2019: 3631-3648 - [i43]Dorottya Demszky, Nikhil Garg, Rob Voigt, James Zou, Matthew Gentzkow, Jesse Shapiro, Dan Jurafsky:
Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootings. CoRR abs/1904.01596 (2019) - [i42]Julia Kruk, Jonah Lubin, Karan Sikka, Xiao Lin, Dan Jurafsky, Ajay Divakaran:
Integrating Text and Image: Determining Multimodal Document Intent in Instagram Posts. CoRR abs/1904.09073 (2019) - [i41]Urvashi Khandelwal, Kevin Clark, Dan Jurafsky, Lukasz Kaiser:
Sample Efficient Text Summarization Using a Single Pre-Trained Transformer. CoRR abs/1905.08836 (2019) - [i40]Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, Mike Lewis:
Generalization through Memorization: Nearest Neighbor Language Models. CoRR abs/1911.00172 (2019) - [i39]Maarten Sap, Saadia Gabriel, Lianhui Qin, Dan Jurafsky, Noah A. Smith, Yejin Choi:
Social Bias Frames: Reasoning about Social and Power Implications of Language. CoRR abs/1911.03891 (2019) - [i38]Reid Pryzant, Richard Diehl Martinez, Nathan Dass, Sadao Kurohashi, Dan Jurafsky, Diyi Yang:
Automatically Neutralizing Subjective Bias in Text. CoRR abs/1911.09709 (2019) - 2018
- [j23]Nikhil Garg, Londa Schiebinger, Dan Jurafsky, James Zou:
Word embeddings quantify 100 years of gender and ethnic stereotypes. Proc. Natl. Acad. Sci. USA 115(16): E3635-E3644 (2018) - [j22]David Jurgens, Srijan Kumar, Raine Hoover, Daniel A. McFarland, Dan Jurafsky:
Measuring the Evolution of a Scientific Field through Citation Frames. Trans. Assoc. Comput. Linguistics 6: 391-406 (2018) - [j21]Vinodkumar Prabhakaran, Camilla Griffiths, Hang Su, Prateek Verma, Nelson Morgan, Jennifer L. Eberhardt, Dan Jurafsky:
Detecting Institutional Dialog Acts in Police Traffic Stops. Trans. Assoc. Comput. Linguistics 6: 467-481 (2018) - [c151]Urvashi Khandelwal, He He, Peng Qi, Dan Jurafsky:
Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context. ACL (1) 2018: 284-294 - [c150]Dan Iter, Jong Yoon, Dan Jurafsky:
Automatic Detection of Incoherent Speech for Diagnosing Schizophrenia. CLPsych@NAACL-HTL 2018: 136-146 - [c149]Michael Hahn, Judith Degen, Noah D. Goodman, Dan Jurafsky, Richard Futrell:
An Information-Theoretic Explanation of Adjective Ordering Preferences. CogSci 2018 - [c148]Matthew Lamm, Arun Tejasvi Chaganty, Christopher D. Manning, Dan Jurafsky, Percy Liang:
Textual Analogy Parsing: What's Shared and What's Compared among Analogous Facts. EMNLP 2018: 82-92 - [c147]Anjalie Field, Doron Kliger, Shuly Wintner, Jennifer Pan, Dan Jurafsky, Yulia Tsvetkov:
Framing and Agenda-Setting in Russian News: a Computational Analysis of Intricate Political Strategies. EMNLP 2018: 3570-3580 - [c146]Reid Pryzant, Youngjoo Chung, Dan Jurafsky, Denny Britz:
JESC: Japanese-English Subtitle Corpus. LREC 2018 - [c145]Rob Voigt, David Jurgens, Vinodkumar Prabhakaran, Dan Jurafsky, Yulia Tsvetkov:
RtGender: A Corpus for Studying Differential Responses to Gender. LREC 2018 - [c144]Ziang Xie, Guillaume Genthial, Stanley Xie, Andrew Y. Ng, Dan Jurafsky:
Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction. NAACL-HLT 2018: 619-628 - [c143]Reid Pryzant, Kelly Shen, Dan Jurafsky, Stefan Wagner:
Deconfounded Lexicon Induction for Interpretable Social Science. NAACL-HLT 2018: 1615-1625 - [c142]William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec:
Embedding Logical Queries on Knowledge Graphs. NeurIPS 2018: 2030-2041 - [c141]Srijan Kumar, William L. Hamilton, Jure Leskovec, Dan Jurafsky:
Community Interaction and Conflict on the Web. WWW 2018: 933-943 - [i37]Srijan Kumar, William L. Hamilton, Jure Leskovec, Dan Jurafsky:
Community Interaction and Conflict on the Web. CoRR abs/1803.03697 (2018) - [i36]Urvashi Khandelwal, He He, Peng Qi, Dan Jurafsky:
Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context. CoRR abs/1805.04623 (2018) - [i35]William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec:
Querying Complex Networks in Vector Space. CoRR abs/1806.01445 (2018) - [i34]Anjalie Field, Doron Kliger, Shuly Wintner, Jennifer Pan, Dan Jurafsky, Yulia Tsvetkov:
Framing and Agenda-setting in Russian News: a Computational Analysis of Intricate Political Strategies. CoRR abs/1808.09386 (2018) - [i33]Matthew Lamm, Arun Tejasvi Chaganty, Christopher D. Manning, Dan Jurafsky, Percy Liang:
Textual Analogy Parsing: What's Shared and What's Compared among Analogous Facts. CoRR abs/1809.02700 (2018) - 2017
- [j20]Andrew L. Maas, Peng Qi, Ziang Xie, Awni Y. Hannun, Christopher T. Lengerich, Daniel Jurafsky, Andrew Y. Ng:
Building DNN acoustic models for large vocabulary speech recognition. Comput. Speech Lang. 41: 195-213 (2017) - [j19]Grace Muzny, Mark Algee-Hewitt, Dan Jurafsky:
Dialogism in the novel: A computational model of the dialogic nature of narration and quotations. Digit. Scholarsh. Humanit. 32(suppl_2): ii31-ii52 (2017) - [j18]Heeyoung Lee, Mihai Surdeanu, Dan Jurafsky:
A scaffolding approach to coreference resolution integrating statistical and rule-based models. Nat. Lang. Eng. 23(5): 733-762 (2017) - [c140]David Jurgens, Yulia Tsvetkov, Dan Jurafsky:
Incorporating Dialectal Variability for Socially Equitable Language Identification. ACL (2) 2017: 51-57 - [c139]Grace Muzny, Michael Fang, Angel X. Chang, Dan Jurafsky:
A Two-stage Sieve Approach for Quote Attribution. EACL (1) 2017: 460-470 - [c138]Jiwei Li, Dan Jurafsky:
Neural Net Models of Open-domain Discourse Coherence. EMNLP 2017: 198-209 - [c137]Jiwei Li, Will Monroe, Tianlin Shi, Sébastien Jean, Alan Ritter, Dan Jurafsky:
Adversarial Learning for Neural Dialogue Generation. EMNLP 2017: 2157-2169 - [c136]Ziang Xie, Sida I. Wang, Jiwei Li, Daniel Lévy, Aiming Nie, Dan Jurafsky, Andrew Y. Ng:
Data Noising as Smoothing in Neural Network Language Models. ICLR (Poster) 2017 - [c135]Justine Zhang, William L. Hamilton, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, Jure Leskovec:
Community Identity and User Engagement in a Multi-Community Landscape. ICWSM 2017: 377-386 - [c134]William L. Hamilton, Justine Zhang, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, Jure Leskovec:
Loyalty in Online Communities. ICWSM 2017: 540-543 - [c133]Reid Pryzant, Youngjoo Chung, Dan Jurafsky:
Predicting Sales from the Language of Product Descriptions. eCOM@SIGIR 2017 - [c132]David Jurgens, Yulia Tsvetkov, Dan Jurafsky:
Writer Profiling Without the Writer's Text. SocInfo (2) 2017: 537-558 - [i32]Jiwei Li, Will Monroe, Tianlin Shi, Alan Ritter, Dan Jurafsky:
Adversarial Learning for Neural Dialogue Generation. CoRR abs/1701.06547 (2017) - [i31]Jiwei Li, Will Monroe, Dan Jurafsky:
Learning to Decode for Future Success. CoRR abs/1701.06549 (2017) - [i30]Jiwei Li, Will Monroe, Dan Jurafsky:
Data Distillation for Controlling Specificity in Dialogue Generation. CoRR abs/1702.06703 (2017) - [i29]Ziang Xie, Sida I. Wang, Jiwei Li, Daniel Lévy, Aiming Nie, Dan Jurafsky, Andrew Y. Ng:
Data Noising as Smoothing in Neural Network Language Models. CoRR abs/1703.02573 (2017) - [i28]William L. Hamilton, Justine Zhang, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, Jure Leskovec:
Loyalty in Online Communities. CoRR abs/1703.03386 (2017) - [i27]Justine Zhang, William L. Hamilton, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, Jure Leskovec:
Community Identity and User Engagement in a Multi-Community Landscape. CoRR abs/1705.09665 (2017) - [i26]Reid Pryzant, Yongjoo Chung, Dan Jurafsky, Denny Britz:
JESC: Japanese-English Subtitle Corpus. CoRR abs/1710.10639 (2017) - [i25]Nikhil Garg, Londa Schiebinger, Dan Jurafsky, James Zou:
Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypes. CoRR abs/1711.08412 (2017) - 2016
- [c131]William L. Hamilton, Jure Leskovec, Dan Jurafsky:
Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change. ACL (1) 2016 - [c130]Vinodkumar Prabhakaran, William L. Hamilton, Daniel A. McFarland, Dan Jurafsky:
Predicting the Rise and Fall of Scientific Topics from Trends in their Rhetorical Framing. ACL (1) 2016 - [c129]Grace Muzny, Mark Algee-Hewitt, Dan Jurafsky:
The Dialogic Turn and the Performance of Gender: the English Canon 1782-2011. DH 2016: 296-299 - [c128]Ruihong Huang, Ignacio Cases, Dan Jurafsky, Cleo Condoravdi, Ellen Riloff:
Distinguishing Past, On-going, and Future Events: The EventStatus Corpus. EMNLP 2016: 44-54 - [c127]William L. Hamilton, Kevin Clark, Jure Leskovec, Dan Jurafsky:
Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora. EMNLP 2016: 595-605 - [c126]Jiwei Li, Will Monroe, Alan Ritter, Dan Jurafsky, Michel Galley, Jianfeng Gao:
Deep Reinforcement Learning for Dialogue Generation. EMNLP 2016: 1192-1202 - [c125]William L. Hamilton, Jure Leskovec, Dan Jurafsky:
Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change. EMNLP 2016: 2116-2121 - [c124]Rob Voigt, Dan Jurafsky, Meghan Sumner:
Between- and Within-Speaker Effects of Bilingualism on F0 Variation. INTERSPEECH 2016: 1122-1126 - [c123]Dan Jurafsky:
Ketchup, Interdisciplinarity, and the Spread of Innovation in Speech and Language Processing. INTERSPEECH 2016: 3111 - [c122]Jiwei Li, Xinlei Chen, Eduard H. Hovy, Dan Jurafsky:
Visualizing and Understanding Neural Models in NLP. HLT-NAACL 2016: 681-691 - [i24]Jiwei Li, Dan Jurafsky:
Mutual Information and Diverse Decoding Improve Neural Machine Translation. CoRR abs/1601.00372 (2016) - [i23]Ziang Xie, Anand Avati, Naveen Arivazhagan, Dan Jurafsky, Andrew Y. Ng:
Neural Language Correction with Character-Based Attention. CoRR abs/1603.09727 (2016) - [i22]William L. Hamilton, Jure Leskovec, Dan Jurafsky:
Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change. CoRR abs/1605.09096 (2016) - [i21]Jiwei Li, Will Monroe, Alan Ritter, Michel Galley, Jianfeng Gao, Dan Jurafsky:
Deep Reinforcement Learning for Dialogue Generation. CoRR abs/1606.01541 (2016) - [i20]Jiwei Li, Dan Jurafsky:
Neural Net Models for Open-Domain Discourse Coherence. CoRR abs/1606.01545 (2016) - [i19]William L. Hamilton, Kevin Clark, Jure Leskovec, Dan Jurafsky:
Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora. CoRR abs/1606.02820 (2016) - [i18]William L. Hamilton, Jure Leskovec, Dan Jurafsky:
Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change. CoRR abs/1606.02821 (2016) - [i17]David Jurgens, Srijan Kumar, Raine Hoover, Daniel A. McFarland, Dan Jurafsky:
Citation Classification for Behavioral Analysis of a Scientific Field. CoRR abs/1609.00435 (2016) - [i16]Jiwei Li, Will Monroe, Dan Jurafsky:
A Simple, Fast Diverse Decoding Algorithm for Neural Generation. CoRR abs/1611.08562 (2016) - [i15]Jiwei Li, Will Monroe, Dan Jurafsky:
Understanding Neural Networks through Representation Erasure. CoRR abs/1612.08220 (2016) - 2015
- [c121]Rob Voigt, Dan Jurafsky:
The Users Who Say 'Ni': Audience Identification in Chinese-language Restaurant Reviews. ACL (2) 2015: 314-319 - [c120]Jiwei Li, Minh-Thang Luong, Dan Jurafsky:
A Hierarchical Neural Autoencoder for Paragraphs and Documents. ACL (1) 2015: 1106-1115 - [c119]Jiwei Li, Dan Jurafsky:
Do Multi-Sense Embeddings Improve Natural Language Understanding? EMNLP 2015: 1722-1732 - [c118]Jiwei Li, Thang Luong, Dan Jurafsky, Eduard H. Hovy:
When Are Tree Structures Necessary for Deep Learning of Representations? EMNLP 2015: 2304-2314 - [c117]Robert Podesva, Patrick Callier, Rob Voigt, Dan Jurafsky:
The connection between smiling and GOAT fronting: Embodied affect in sociophonetic variation. ICPhS 2015 - [c116]Andrew L. Maas, Ziang Xie, Dan Jurafsky, Andrew Y. Ng:
Lexicon-Free Conversational Speech Recognition with Neural Networks. HLT-NAACL 2015: 345-354 - [i14]Jiwei Li, Dan Jurafsky, Eduard H. Hovy:
When Are Tree Structures Necessary for Deep Learning of Representations? CoRR abs/1503.00185 (2015) - [i13]Jiwei Li, Minh-Thang Luong, Dan Jurafsky:
A Hierarchical Neural Autoencoder for Paragraphs and Documents. CoRR abs/1506.01057 (2015) - [i12]Jiwei Li, Xinlei Chen, Eduard H. Hovy, Dan Jurafsky:
Visualizing and Understanding Neural Models in NLP. CoRR abs/1506.01066 (2015) - [i11]Jiwei Li, Dan Jurafsky:
Do Multi-Sense Embeddings Improve Natural Language Understanding? CoRR abs/1506.01070 (2015) - [i10]Jiwei Li, Alan Ritter, Dan Jurafsky:
Learning multi-faceted representations of individuals from heterogeneous evidence using neural networks. CoRR abs/1510.05198 (2015) - 2014
- [j17]Dan Jurafsky:
Charles J. Fillmore. Comput. Linguistics 40(3): 725-731 (2014) - [j16]Dan Jurafsky, Victor Chahuneau, Bryan R. Routledge, Noah A. Smith:
Narrative framing of consumer sentiment in online restaurant reviews. First Monday 19(4) (2014) - [c115]Elie Bursztein, Angelique Moscicki, Celine Fabry, Steven Bethard, John C. Mitchell, Dan Jurafsky:
Easy does it: more usable CAPTCHAs. CHI 2014: 2637-2646 - [c114]Adam Vogel, Andrés Goméz Emilsson, Michael C. Frank, Dan Jurafsky, Christopher Potts:
Learning to Reason Pragmatically with Cognitive Limitations. CogSci 2014 - [c113]Tim Althoff, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky:
How to Ask for a Favor: A Case Study on the Success of Altruistic Requests. ICWSM 2014 - [c112]Heeyoung Lee, Mihai Surdeanu, Bill MacCartney, Dan Jurafsky:
On the Importance of Text Analysis for Stock Price Prediction. LREC 2014: 1170-1175 - [c111]Kevin Reschke, Martin Jankowiak, Mihai Surdeanu, Christopher D. Manning, Daniel Jurafsky:
Event Extraction Using Distant Supervision. LREC 2014: 4527-4531 - [c110]Sebastian Schuster, Stephanie Pancoast, Milind Ganjoo, Michael C. Frank, Dan Jurafsky:
Speaker-independent detection of child-directed speech. SLT 2014: 366-371 - [i9]Tim Althoff, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky:
How to Ask for a Favor: A Case Study on the Success of Altruistic Requests. CoRR abs/1405.3282 (2014) - [i8]Andrew L. Maas, Awni Y. Hannun, Christopher T. Lengerich, Peng Qi, Daniel Jurafsky, Andrew Y. Ng:
Increasing Deep Neural Network Acoustic Model Size for Large Vocabulary Continuous Speech Recognition. CoRR abs/1406.7806 (2014) - [i7]Andrew L. Maas, Awni Y. Hannun, Daniel Jurafsky, Andrew Y. Ng:
First-Pass Large Vocabulary Continuous Speech Recognition using Bi-Directional Recurrent DNNs. CoRR abs/1408.2873 (2014) - [i6]Jiwei Li, Alan Ritter, Dan Jurafsky:
Inferring User Preferences by Probabilistic Logical Reasoning over Social Networks. CoRR abs/1411.2679 (2014) - 2013
- [j15]Heeyoung Lee, Angel X. Chang, Yves Peirsman, Nathanael Chambers, Mihai Surdeanu, Dan Jurafsky:
Deterministic Coreference Resolution Based on Entity-Centric, Precision-Ranked Rules. Comput. Linguistics 39(4): 885-916 (2013) - [j14]Rajesh Ranganath, Dan Jurafsky, Daniel A. McFarland:
Detecting friendly, flirtatious, awkward, and assertive speech in speed-dates. Comput. Speech Lang. 27(1): 89-115 (2013) - [c109]Adam Vogel, Christopher Potts, Dan Jurafsky:
Implicatures and Nested Beliefs in Approximate Decentralized-POMDPs. ACL (2) 2013: 74-80 - [c108]Cristian Danescu-Niculescu-Mizil, Moritz Sudhof, Dan Jurafsky, Jure Leskovec, Christopher Potts:
A computational approach to politeness with application to social factors. ACL (1) 2013: 250-259 - [c107]Kevin Reschke, Adam Vogel, Dan Jurafsky:
Generating Recommendation Dialogs by Extracting Information from User Reviews. ACL (2) 2013: 499-504 - [c106]Marta Recasens, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky:
Linguistic Models for Analyzing and Detecting Biased Language. ACL (1) 2013: 1650-1659 - [c105]Rob Voigt, Dan Jurafsky:
Tradition and Modernity in 20th Century Chinese Poetry. CLfL@NAACL-HLT 2013: 17-22 - [c104]Valentin I. Spitkovsky, Hiyan Alshawi, Daniel Jurafsky:
Breaking Out of Local Optima with Count Transforms and Model Recombination: A Study in Grammar Induction. EMNLP 2013: 1983-1995 - [c103]Marta Recasens, Matthew Can, Daniel Jurafsky:
Same Referent, Different Words: Unsupervised Mining of Opaque Coreferent Mentions. HLT-NAACL 2013: 897-906 - [c102]Adam Vogel, Max Bodoia, Christopher Potts, Daniel Jurafsky:
Emergence of Gricean Maxims from Multi-Agent Decision Theory. HLT-NAACL 2013: 1072-1081 - [c101]Daniel M. Cer, Christopher D. Manning, Dan Jurafsky:
Positive Diversity Tuning for Machine Translation System Combination. WMT@ACL 2013: 320-328 - [c100]Cristian Danescu-Niculescu-Mizil, Robert West, Dan Jurafsky, Jure Leskovec, Christopher Potts:
No country for old members: user lifecycle and linguistic change in online communities. WWW 2013: 307-318 - [i5]Cristian Danescu-Niculescu-Mizil, Moritz Sudhof, Dan Jurafsky, Jure Leskovec, Christopher Potts:
A Computational Approach to Politeness with Application to Social Factors. CoRR abs/1306.6078 (2013) - 2012
- [j13]Michael Levin, Stefan Krawczyk, Steven Bethard, Dan Jurafsky:
Citation-based bootstrapping for large-scale author disambiguation. J. Assoc. Inf. Sci. Technol. 63(5): 1030-1047 (2012) - [c99]Ashton Anderson, Dan Jurafsky, Daniel A. McFarland:
Towards a Computational History of the ACL: 1980-2008. Discoveries@ACL 2012: 13-21 - [c98]Adam Vogel, Dan Jurafsky:
He Said, She Said: Gender in the ACL Anthology. Discoveries@ACL 2012: 33-41 - [c97]Justine Kao, Dan Jurafsky:
A Computational Analysis of Style, Affect, and Imagery in Contemporary Poetry. CLfL@NAACL-HLT 2012: 8-17 - [c96]Rob Voigt, Dan Jurafsky:
Towards a Literary Machine Translation: The Role of Referential Cohesion. CLfL@NAACL-HLT 2012: 18-25 - [c95]Heeyoung Lee, Marta Recasens, Angel X. Chang, Mihai Surdeanu, Dan Jurafsky:
Joint Entity and Event Coreference Resolution across Documents. EMNLP-CoNLL 2012: 489-500 - [c94]Valentin I. Spitkovsky, Hiyan Alshawi, Daniel Jurafsky:
Three Dependency-and-Boundary Models for Grammar Induction. EMNLP-CoNLL 2012: 688-698 - [c93]Julian J. McAuley, Jure Leskovec, Dan Jurafsky:
Learning Attitudes and Attributes from Multi-aspect Reviews. ICDM 2012: 1020-1025 - [c92]Nathanael Chambers, Dan Jurafsky:
Learning the Central Events and Participants in Unlabeled Text. ICML 2012 - [c91]Gabor Angeli, Christopher D. Manning, Daniel Jurafsky:
Parsing Time: Learning to Interpret Time Expressions. HLT-NAACL 2012: 446-455 - [c90]Valentin I. Spitkovsky, Hiyan Alshawi, Daniel Jurafsky:
Bootstrapping Dependency Grammar Inducers from Incomplete Sentence Fragments via Austere Models. ICGI 2012: 189-194 - [i4]Julian J. McAuley, Jure Leskovec, Dan Jurafsky:
Learning Attitudes and Attributes from Multi-Aspect Reviews. CoRR abs/1210.3926 (2012) - 2011
- [c89]Nathanael Chambers, Dan Jurafsky:
Template-Based Information Extraction without the Templates. ACL 2011: 976-986 - [c88]Valentin I. Spitkovsky, Hiyan Alshawi, Daniel Jurafsky:
Punctuation: Making a Point in Unsupervised Dependency Parsing. CoNLL 2011: 19-28 - [c87]Heeyoung Lee, Yves Peirsman, Angel X. Chang, Nathanael Chambers, Mihai Surdeanu, Dan Jurafsky:
Stanford's Multi-Pass Sieve Coreference Resolution System at the CoNLL-2011 Shared Task. CoNLL Shared Task 2011: 28-34 - [c86]Valentin I. Spitkovsky, Hiyan Alshawi, Daniel Jurafsky:
Lateen EM: Unsupervised Training with Multiple Objectives, Applied to Dependency Grammar Induction. EMNLP 2011: 1269-1280 - [c85]Valentin I. Spitkovsky, Hiyan Alshawi, Angel X. Chang, Daniel Jurafsky:
Unsupervised Dependency Parsing without Gold Part-of-Speech Tags. EMNLP 2011: 1281-1290 - [c84]Ramesh Nallapati, Xiaolin Shi, Daniel A. McFarland, Jure Leskovec, Daniel Jurafsky:
LeadLag LDA: Estimating Topic Specific Leads and Lags of Information Outlets. ICWSM 2011 - [c83]Andrey Gusev, Nathanael Chambers, Divye Raj Khilnani, Pranav Khaitan, Steven Bethard, Dan Jurafsky:
Using Query Patterns to Learn the Duration of Events. IWCS 2011 - [c82]Nikhil Johri, Daniel Ramage, Daniel A. McFarland, Daniel Jurafsky:
A Study of Academic Collaborations in Computational Linguistics using a Latent Mixture of Authors Model. LaTeCH@ACL 2011: 124-132 - [c81]Dan Jurafsky:
Sex, food, and words: the hidden meanings behind everyday language. UIST 2011: 429-430 - 2010
- [j12]Sasha Calhoun, Jean Carletta, Jason M. Brenier, Neil Mayo, Dan Jurafsky, Mark Steedman, David Beaver:
The NXT-format Switchboard Corpus: a rich resource for investigating the syntax, semantics, pragmatics and prosody of dialogue. Lang. Resour. Evaluation 44(4): 387-419 (2010) - [j11]Sharon Goldwater, Daniel Jurafsky, Christopher D. Manning:
Which words are hard to recognize? Prosodic, lexical, and disfluency factors that increase speech recognition error rates. Speech Commun. 52(3): 181-200 (2010) - [c80]Adam Vogel, Karthik Raghunathan, Dan Jurafsky:
Eye Spy: Improving Vision through Dialog. AAAI Fall Symposium: Dialog with Robots 2010 - [c79]Nathanael Chambers, Daniel Jurafsky:
Improving the Use of Pseudo-Words for Evaluating Selectional Preferences. ACL 2010: 445-453 - [c78]Adam Vogel, Daniel Jurafsky:
Learning to Follow Navigational Directions. ACL 2010: 806-814 - [c77]Valentin I. Spitkovsky, Daniel Jurafsky, Hiyan Alshawi:
Profiting from Mark-Up: Hyper-Text Annotations for Guided Parsing. ACL 2010: 1278-1287 - [c76]Steven Bethard, Dan Jurafsky:
Who should I cite: learning literature search models from citation behavior. CIKM 2010: 609-618 - [c75]Valentin I. Spitkovsky, Hiyan Alshawi, Daniel Jurafsky, Christopher D. Manning:
Viterbi Training Improves Unsupervised Dependency Parsing. CoNLL 2010: 9-17 - [c74]Karthik Raghunathan, Heeyoung Lee, Sudarshan Rangarajan, Nate Chambers, Mihai Surdeanu, Dan Jurafsky, Christopher D. Manning:
A Multi-Pass Sieve for Coreference Resolution. EMNLP 2010: 492-501 - [c73]Daniel M. Cer, Marie-Catherine de Marneffe, Daniel Jurafsky, Christopher D. Manning:
Parsing to Stanford Dependencies: Trade-offs between Speed and Accuracy. LREC 2010 - [c72]Nathanael Chambers, Daniel Jurafsky:
A Database of Narrative Schemas. LREC 2010 - [c71]Daniel M. Cer, Michel Galley, Daniel Jurafsky, Christopher D. Manning:
Phrasal: A Statistical Machine Translation Toolkit for Exploring New Model Features. NAACL (Demos) 2010: 9-12 - [c70]Daniel M. Cer, Christopher D. Manning, Daniel Jurafsky:
The Best Lexical Metric for Phrase-Based Statistical MT System Optimization. HLT-NAACL 2010: 555-563 - [c69]Valentin I. Spitkovsky, Hiyan Alshawi, Daniel Jurafsky:
From Baby Steps to Leapfrog: How "Less is More" in Unsupervised Dependency Parsing. HLT-NAACL 2010: 751-759 - [c68]Elie Bursztein, Steven Bethard, Celine Fabry, John C. Mitchell, Daniel Jurafsky:
How Good Are Humans at Solving CAPTCHAs? A Large Scale Evaluation. IEEE Symposium on Security and Privacy 2010: 399-413 - [e3]Chu-Ren Huang, Dan Jurafsky:
COLING 2010, 23rd International Conference on Computational Linguistics, Proceedings of the Conference, 23-27 August 2010, Beijing, China. Tsinghua University Press 2010 [contents] - [e2]Chu-Ren Huang, Dan Jurafsky:
COLING 2010, 23rd International Conference on Computational Linguistics, Posters Volume, 23-27 August 2010, Beijing, China. Chinese Information Processing Society of China 2010 [contents]
2000 – 2009
- 2009
- [b2]Dan Jurafsky, James H. Martin:
Speech and language processing: an introduction to natural language processing, computational linguistics, and speech recognition, 2nd Edition. Prentice Hall series in artificial intelligence, Prentice Hall, Pearson Education International 2009, ISBN 9780135041963, pp. 1-1024 - [j10]Yuan Zhao, Dan Jurafsky:
The effect of lexical frequency and Lombard reflex on tone hyperarticulation. J. Phonetics 37(2): 231-247 (2009) - [j9]Sebastian Padó, Daniel M. Cer, Michel Galley, Dan Jurafsky, Christopher D. Manning:
Measuring machine translation quality as semantic equivalence: A metric based on entailment features. Mach. Transl. 23(2-3): 181-193 (2009) - [c67]Sebastian Padó, Michel Galley, Daniel Jurafsky, Christopher D. Manning:
Robust Machine Translation Evaluation with Entailment Features. ACL/IJCNLP 2009: 297-305 - [c66]Nathanael Chambers, Dan Jurafsky:
Unsupervised Learning of Narrative Schemas and their Participants. ACL/IJCNLP 2009: 602-610 - [c65]Mike Mintz, Steven Bills, Rion Snow, Daniel Jurafsky:
Distant supervision for relation extraction without labeled data. ACL/IJCNLP 2009: 1003-1011 - [c64]Daniel Jurafsky:
It's not you, it's me: Automatically extracting social meaning from speed dates. ASRU 2009: 11 - [c63]Yun-Hsuan Sung, Daniel Jurafsky:
Hidden Conditional Random Fields for phone recognition. ASRU 2009: 107-112 - [c62]Rajesh Ranganath, Daniel Jurafsky, Daniel A. McFarland:
It's Not You, it's Me: Detecting Flirting and its Misperception in Speed-Dates. EMNLP 2009: 334-342 - [c61]Daniel Jurafsky, Rajesh Ranganath, Daniel A. McFarland:
Extracting Social Meaning: Identifying Interactional Style in Spoken Conversation. HLT-NAACL 2009: 638-646 - [c60]Pi-Chuan Chang, Huihsin Tseng, Dan Jurafsky, Christopher D. Manning:
Discriminative Reordering with Chinese Grammatical Relations Features. SSST@HLT-NAACL 2009: 51-59 - [c59]Sebastian Padó, Michel Galley, Daniel Jurafsky, Christopher D. Manning:
Machine Translation Evaluation with Textual Entailment Features. WMT@EACL 2009: 37-41 - [c58]Pi-Chuan Chang, Daniel Jurafsky, Christopher D. Manning:
Disambiguating "DE" for Chinese-English Machine Translation. WMT@EACL 2009: 215-223 - [i3]Eneko Agirre, Angel X. Chang, Daniel Jurafsky, Christopher D. Manning, Valentin I. Spitkovsky, Eric Yeh:
Stanford-UBC at TAC-KBP. TAC 2009 - 2008
- [c57]Sharon Goldwater, Daniel Jurafsky, Christopher D. Manning:
Which Words Are Hard to Recognize? Prosodic, Lexical, and Disfluency Factors that Increase ASR Error Rates. ACL 2008: 380-388 - [c56]Nathanael Chambers, Daniel Jurafsky:
Unsupervised Learning of Narrative Event Chains. ACL 2008: 789-797 - [c55]Rion Snow, Brendan O'Connor, Daniel Jurafsky, Andrew Y. Ng:
Cheap and Fast - But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks. EMNLP 2008: 254-263 - [c54]David Hall, Daniel Jurafsky, Christopher D. Manning:
Studying the History of Ideas Using Topic Models. EMNLP 2008: 363-371 - [c53]Nathanael Chambers, Daniel Jurafsky:
Jointly Combining Implicit Constraints Improves Temporal Ordering. EMNLP 2008: 698-706 - [c52]Yun-Hsuan Sung, Constantinos Boulis, Daniel Jurafsky:
Maximum conditional likelihood linear regression and maximum a posteriori for hidden conditional random fields speaker adaptation. ICASSP 2008: 4293-4296 - [c51]Daniel M. Cer, Dan Jurafsky, Christopher D. Manning:
Regularization and Search for Minimum Error Rate Training. WMT@ACL 2008: 26-34 - 2007
- [c50]Nathanael Chambers, Shan Wang, Daniel Jurafsky:
Classifying Temporal Relations Between Events. ACL 2007 - [c49]Surabhi Gupta, Ani Nenkova, Daniel Jurafsky:
Measuring Importance and Query Relevance in Topic-focused Multi-document Summarization. ACL 2007 - [c48]Surabhi Gupta, Matthew Purver, Daniel Jurafsky:
Disambiguating Between Generic and Referential "You" in Dialog. ACL 2007 - [c47]Ani Nenkova, Dan Jurafsky:
Automatic detection of contrastive elements in spontaneous speech. ASRU 2007: 201-206 - [c46]Yun-Hsuan Sung, Constantinos Boulis, Christopher D. Manning, Dan Jurafsky:
Regularization, adaptation, and non-independent features improve hidden conditional random fields for phone classification. ASRU 2007: 347-352 - [c45]Rion Snow, Sushant Prakash, Daniel Jurafsky, Andrew Y. Ng:
Learning to Merge Word Senses. EMNLP-CoNLL 2007: 1005-1014 - [c44]Volker Strom, Ani Nenkova, Robert A. J. Clark, Yolanda Vazquez-Alvarez, Jason M. Brenier, Simon King, Dan Jurafsky:
Modelling prominence and emphasis improves unit-selection synthesis. INTERSPEECH 2007: 1282-1285 - [c43]Ani Nenkova, Jason M. Brenier, Anubha Kothari, Sasha Calhoun, Laura Whitton, David Beaver, Daniel Jurafsky:
To Memorize or to Predict: Prominence labeling in Conversational Speech. HLT-NAACL 2007: 9-16 - [c42]Surabhi Gupta, John Niekrasz, Matthew Purver, Dan Jurafsky:
Resolving "You" in Multi-Party Dialog. SIGdial 2007: 227-230 - 2006
- [j8]Jing Li, Thomas Zheng, William Byrne, Daniel Jurafsky:
A Dialectal Chinese Speech Recognition Framework. J. Comput. Sci. Technol. 21(1): 106-115 (2006) - [c41]Rion Snow, Daniel Jurafsky, Andrew Y. Ng:
Semantic Taxonomy Induction from Heterogenous Evidence. ACL 2006 - [c40]Cheng-Tao Chu, Yun-Hsuan Sung, Yuan Zhao, Daniel Jurafsky:
Detection of word fragments in Mandarin telephone conversation. INTERSPEECH 2006 - [c39]Constance Clarke, Daniel Jurafsky:
Limitations of MLLR adaptation with Spanish-accented English: an error analysis. INTERSPEECH 2006 - [c38]Filip Krsmanovic, Curtis Spencer, Daniel Jurafsky, Andrew Y. Ng:
Have we met? MDP based speaker ID for robot dialogue. INTERSPEECH 2006 - [c37]Jason M. Brenier, Ani Nenkova, Anubha Kothari, Laura Whitton, David Beaver, Dan Jurafsky:
The (Non)Utility of Linguistic Features for Predicting prominence in spontaneous speech. SLT 2006: 54-57 - [p1]Steven Bethard, Hong Yu, Ashley Thornton, Vasileios Hatzivassiloglou, Dan Jurafsky:
Extracting Opinion Propositions and Opinion Holders using Syntactic and Lexical Cues. Computing Attitude and Affect in Text 2006: 125-141 - [e1]Dan Jurafsky, Éric Gaussier:
EMNLP 2006, Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, 22-23 July 2006, Sydney, Australia. ACL 2006, ISBN 1-932432-73-6 [contents] - 2005
- [j7]Sameer S. Pradhan, Kadri Hacioglu, Valerie Krugler, Wayne H. Ward, James H. Martin, Daniel Jurafsky:
Support Vector Learning for Semantic Argument Classification. Mach. Learn. 60(1-3): 11-39 (2005) - [j6]Eric Fosler-Lussier, William Byrne, Daniel Jurafsky:
Editorial. Speech Commun. 46(2): 117-118 (2005) - [c36]Sameer S. Pradhan, Wayne H. Ward, Kadri Hacioglu, James H. Martin, Daniel Jurafsky:
Semantic Role Labeling Using Different Syntactic Views. ACL 2005: 581-588 - [c35]Huihsin Tseng, Pi-Chuan Chang, Galen Andrew, Daniel Jurafsky, Christopher D. Manning:
A Conditional Random Field Word Segmenter for Sighan Bakeoff 2005. SIGHAN@IJCNLP 2005 2005 - [c34]Huihsin Tseng, Daniel Jurafsky, Christopher D. Manning:
Morphological features help POS tagging of unknown words across language varieties. SIGHAN@IJCNLP 2005 2005 - [c33]Sameer Pradhan, Kadri Hacioglu, Wayne H. Ward, James H. Martin, Daniel Jurafsky:
Semantic Role Chunking Combining Complementary Syntactic Views. CoNLL 2005: 217-220 - [c32]Yuan Zhao, Dan Jurafsky:
A preliminary study of Mandarin filled pauses. DiSS 2005: 179-182 - [c31]Yanli Zheng, Richard Sproat, Liang Gu, Izhak Shafran, Haolang Zhou, Yi Su, Daniel Jurafsky, Rebecca Starr, Su-Youn Yoon:
Accent detection and speech recognition for Shanghai-accented Mandarin. INTERSPEECH 2005: 217-220 - [c30]Jiahong Yuan, Jason M. Brenier, Daniel Jurafsky:
Pitch accent prediction: effects of genre and speaker. INTERSPEECH 2005: 1409-1412 - [c29]Jason M. Brenier, Daniel M. Cer, Daniel Jurafsky:
The detection of emphatic words using acoustic and lexical features. INTERSPEECH 2005: 3297-3300 - 2004
- [c28]Kadri Hacioglu, Sameer Pradhan, Wayne H. Ward, James H. Martin, Daniel Jurafsky:
Semantic Role Labeling by Tagging Syntactic Chunks. CoNLL 2004: 110-113 - [c27]Mona T. Diab, Kadri Hacioglu, Daniel Jurafsky:
Automatic Tagging of Arabic Text: From Raw Text to Base Phrase Chunks. HLT-NAACL (Short Papers) 2004 - [c26]Sameer Pradhan, Honglin Sun, Wayne H. Ward, James H. Martin, Daniel Jurafsky:
Parsing Arguments of Nominalizations in English and Chinese. HLT-NAACL (Short Papers) 2004 - [c25]Sameer S. Pradhan, Wayne H. Ward, Kadri Hacioglu, James H. Martin, Daniel Jurafsky:
Shallow Semantic Parsing using Support Vector Machines. HLT-NAACL 2004: 233-240 - [c24]Honglin Sun, Daniel Jurafsky:
Shallow Semantc Parsing of Chinese. HLT-NAACL 2004: 249-256 - [c23]Rion Snow, Daniel Jurafsky, Andrew Y. Ng:
Learning Syntactic Patterns for Automatic Hypernym Discovery. NIPS 2004: 1297-1304 - 2003
- [c22]Honglin Sun, Dan Jurafsky:
The Effect of Rhythm on Structural Disambiguation in Chinese. SIGHAN 2003: 39-46 - [c21]Sameer S. Pradhan, Kadri Hacioglu, Wayne H. Ward, James H. Martin, Daniel Jurafsky:
Semantic Role Parsing: Adding Semantic Structure to Unstructured Text. ICDM 2003: 629-632 - 2002
- [j5]Daniel Gildea, Daniel Jurafsky:
Automatic Labeling of Semantic Roles. Comput. Linguistics 28(3): 245-288 (2002) - [c20]Sameer S. Pradhan, Valerie Krugler, Steven Bethard, Wayne H. Ward, Daniel Jurafsky, James H. Martin, Sasha Blair-Goldensohn, Andrew Hazen Schlaikjer, Elena Filatova, Pablo Ariel Duboue, Hong Yu, Rebecca J. Passonneau, Vasileios Hatzivassiloglou, Kathleen R. McKeown, Gabriel Illouz:
Building a Foundation System for Producing Short Answers to Factual Questions. TREC 2002 - 2001
- [c19]Patrick Schone, Daniel Jurafsky:
Is Knowledge-Free Induction of Multiword Unit Dictionary Headwords a Solved Problem? EMNLP 2001 - [c18]Dan Jurafsky, Wayne H. Ward, Zhang Banping, Keith Herold, Xiuyang Yu, Zhang Sen:
What kind of pronunciation variation is hard for triphones to model? ICASSP 2001: 577-580 - [c17]Daniel Jurafsky, Alan Bell, Michelle Gregory, William D. Raymond:
The effect of language model probability on pronunciation reduction. ICASSP 2001: 801-804 - [c16]Patrick Schone, Daniel Jurafsky:
Knowledge-Free Induction of Inflectional Morphologies. NAACL 2001 - [c15]S. Narayanan, Daniel Jurafsky:
A Bayesian Model Predicts Human Parse Preference and Reading Times in Sentence Processing. NIPS 2001: 59-65 - 2000
- [b1]Daniel Jurafsky, James H. Martin:
Speech and language processing - an introduction to natural language processing, computational linguistics, and speech recognition. Prentice Hall series in artificial intelligence, Prentice Hall 2000, ISBN 978-0-13-095069-7, pp. I-XXVI, 1-934 - [j4]Andreas Stolcke, Klaus Ries, Noah Coccaro, Elizabeth Shriberg, Rebecca A. Bates, Daniel Jurafsky, Paul Taylor, Rachel Martin, Carol Van Ess-Dykema, Marie Meteer:
Dialog Act Modeling for Automatic Tagging and Recognition of Conversational Speech. Comput. Linguistics 26(3): 339-373 (2000) - [c14]Daniel Gildea, Daniel Jurafsky:
Automatic Labeling of Semantic Roles. ACL 2000: 512-520 - [c13]Patrick Schone, Daniel Jurafsky:
Knowledge-Free Induction of Morphology Using Latent Semantic Analysis. CoNLL/LLL 2000: 67-72 - [i2]Andreas Stolcke, Klaus Ries, Noah Coccaro, Elizabeth Shriberg, Rebecca A. Bates, Daniel Jurafsky, Paul Taylor, Rachel Martin, Carol Van Ess-Dykema, Marie Meteer:
Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech. CoRR cs.CL/0006023 (2000) - [i1]Elizabeth Shriberg, Rebecca A. Bates, Andreas Stolcke, Paul Taylor, Daniel Jurafsky, Klaus Ries, Noah Coccaro, Rachel Martin, Marie Meteer, Carol Van Ess-Dykema:
Can Prosody Aid the Automatic Classification of Dialog Acts in Conversational Speech? CoRR cs.CL/0006024 (2000)
1990 – 1999
- 1998
- [c12]Douglas Roland, Daniel Jurafsky:
How Verb Subcategorization Frequencies Are Affected By Corpus Choice. COLING-ACL 1998: 1122-1128 - [c11]Noah Coccaro, Daniel Jurafsky:
Towards better integration of semantic predictors in statistical language modeling. ICSLP 1998 - [c10]Daniel Jurafsky, Alan Bell, Eric Fosler-Lussier, Cynthia Girand, William D. Raymond:
Reduction of English function words in switchboard. ICSLP 1998 - [c9]Charles J. Fillmore, Nancy Ide, Daniel Jurafsky, Catherine Macleod:
An American national corpus: a proposal. LREC 1998: 965-970 - 1996
- [j3]Daniel Jurafsky:
A Probabilistic Model of Lexical and Syntactic Access and Disambiguation. Cogn. Sci. 20(2): 137-194 (1996) - [j2]Daniel Gildea, Daniel Jurafsky:
Learning Bias and Phonological-Rule Induction. Comput. Linguistics 22(4): 497-530 (1996) - 1995
- [c8]Gary N. Tajchman, Daniel Jurafsky, Eric Fosler:
Learning Phonological Rule Probabilities from Speech Corpora with Exploratory Computational Phonology. ACL 1995: 1-8 - [c7]Daniel Gildea, Daniel Jurafsky:
Automatic Induction of Finite State Transducers for Simple Phonological Rules. ACL 1995: 9-15 - [c6]Daniel Jurafsky, Chuck Wooters, Jonathan Segal, Andreas Stolcke, Eric Fosler, Gary N. Tajchman, Nelson Morgan:
Using a stochastic context-free grammar as a language model for speech recognition. ICASSP 1995: 189-192 - [c5]Gary N. Tajchman, Eric Fosler, Daniel Jurafsky:
Building multiple pronunciation models for novel words using exploratory computational phonology. EUROSPEECH 1995: 2247-2250 - 1994
- [c4]Daniel Jurafsky, Chuck Wooters, Gary N. Tajchman, Jonathan Segal, Andreas Stolcke, Eric Fosler, Nelson Morgan:
The berkeley restaurant project. ICSLP 1994: 2139-2142 - 1992
- [c3]Daniel Jurafsky:
An On-Line Computational Model of Human Sentence Interpretation. AAAI 1992: 302-308 - 1990
- [c2]Daniel Jurafsky:
Representing and Integrating Linguistic Knowledge. COLING 1990: 199-204
1980 – 1989
- 1989
- [j1]Daniel Jurafsky:
James Allen, Understanding Natural Language. Artif. Intell. 38(3): 367-377 (1989) - 1988
- [c1]Daniel Jurafsky:
Issues in Relating Syntax Semantics. COLING 1988: 278-284
Coauthor Index
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