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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 20 of 20 1 Learning the Ordering of Coordinate Compounds and Elaborate Expressions in Hmong, Lahu, and Chinese ... Cui, Chenxuan; Zhang, Katherine J.; Mortensen, David R.. - : arXiv, 2022 BASE Show details 2 AUTOLEX: An Automatic Framework for Linguistic Exploration ... Chaudhary, Aditi; Sheikh, Zaid; Mortensen, David R. - : arXiv, 2022 BASE Show details 3 Evaluating the Morphosyntactic Well-formedness of Generated Texts ... Pratapa, Adithya; Anastasopoulos, Antonios; Rijhwani, Shruti. - : arXiv, 2021 BASE Show details 4 Tusom2021: A Phonetically Transcribed Speech Dataset from an Endangered Language for Universal Phone Recognition Experiments ... Mortensen, David R.; Picone, Jordan; Li, Xinjian. - : arXiv, 2021 BASE Show details 5 Evaluating the Morphosyntactic Well-formedness of Generated Texts ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Anastasopoulos, Antonios; Chaudhary, Aditi. - : Underline Science Inc., 2021 BASE Show details 6 Differentiable Allophone Graphs for Language-Universal Speech Recognition ... Yan, Brian; Dalmia, Siddharth; Mortensen, David R.. - : arXiv, 2021 BASE Show details 7 AlloVera: A Multilingual Allophone Database ... Mortensen, David R.; Li, Xinjian; Littell, Patrick. - : arXiv, 2020 BASE Show details 8 Towards Zero-shot Learning for Automatic Phonemic Transcription ... Li, Xinjian; Dalmia, Siddharth; Mortensen, David R.. - : arXiv, 2020 BASE Show details 9 Automatic Extraction of Rules Governing Morphological Agreement ... Chaudhary, Aditi; Anastasopoulos, Antonios; Pratapa, Adithya. - : arXiv, 2020 BASE Show details 10 Where New Words Are Born: Distributional Semantic Analysis of Neologisms and Their Semantic Neighborhoods ... Ryskina, Maria; Rabinovich, Ella; Berg-Kirkpatrick, Taylor. - : arXiv, 2020 BASE Show details 11 Universal Phone Recognition with a Multilingual Allophone System ... Li, Xinjian; Dalmia, Siddharth; Li, Juncheng. - : arXiv, 2020 BASE Show details 12 Cross-Cultural Similarity Features for Cross-Lingual Transfer Learning of Pragmatically Motivated Tasks ... Sun, Jimin; Ahn, Hwijeen; Park, Chan Young. - : arXiv, 2020 BASE Show details 13 Characterizing Sociolinguistic Variation in the Competing Vaccination Communities ... Memon, Shahan Ali; Tyagi, Aman; Mortensen, David R.. - : arXiv, 2020 BASE Show details 14 Where New Words Are Born: Distributional Semantic Analysis of Neologisms and Their Semantic Neighborhoods Ryskina, Maria; Rabinovich, Ella; Berg-Kirkpatrick, Taylor... In: Proceedings of the Society for Computation in Linguistics (2020) BASE Show details 15 Using Interlinear Glosses as Pivot in Low-Resource Multilingual Machine Translation ... Zhou, Zhong; Levin, Lori; Mortensen, David R.. - : arXiv, 2019 BASE Show details 16 Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations ... Chaudhary, Aditi; Zhou, Chunting; Levin, Lori; Neubig, Graham; Mortensen, David R.; Carbonell, Jaime G.. - : arXiv, 2018 Abstract: Much work in Natural Language Processing (NLP) has been for resource-rich languages, making generalization to new, less-resourced languages challenging. We present two approaches for improving generalization to low-resourced languages by adapting continuous word representations using linguistically motivated subword units: phonemes, morphemes and graphemes. Our method requires neither parallel corpora nor bilingual dictionaries and provides a significant gain in performance over previous methods relying on these resources. We demonstrate the effectiveness of our approaches on Named Entity Recognition for four languages, namely Uyghur, Turkish, Bengali and Hindi, of which Uyghur and Bengali are low resource languages, and also perform experiments on Machine Translation. Exploiting subwords with transfer learning gives us a boost of +15.2 NER F1 for Uyghur and +9.7 F1 for Bengali. We also show improvements in the monolingual setting where we achieve (avg.) +3 F1 and (avg.) +1.35 BLEU. ... : Accepted at EMNLP 2018 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1808.09500 https://dx.doi.org/10.48550/arxiv.1808.09500 BASE Hide details 17 Lexical Prefixes and Tibeto-Burman Laryngeal Contrasts Mortensen, David R In: Mortensen, David R. (2013). Lexical Prefixes and Tibeto-Burman Laryngeal Contrasts. Proceedings of the 37th Annual Meeting of the Berkeley Linguistics Society, 37(37), 272 - 286. Retrieved from: http://www.escholarship.org/uc/item/1229x8bj (2013) BASE Show details 18 The emergence of obstruents after high vowels Mortensen, David R. In: Diachronica. - Amsterdam [u.a.] : Benjamins 29 (2012) 4, 434-470 BLLDB OLC Linguistik Show details 19 A classification of compounds in American Sign Language: an evaluation of the Bisetto and Scalise framework Mortensen, David R.; Vercellotti, Mary Lou In: Morphology. - Heidelberg [u.a.] : Springer 22 (2012) 4, 545-579 BLLDB OLC Linguistik Show details 20 Lexical prefixes and Tibeto-Burman laryngeal contrasts Mortensen, David R. In: Annual Meeting of the Berkeley Linguistics Society; BLS 37: General Session and Parasession on Language, Gender, and Sexuality; 272-286 ; 2377-1666 ; 0363-2946 (2011) BASE Show details

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