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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 – 12 of 12 1 Unsupervised Translation of German--Lower Sorbian: Exploring Training and Novel Transfer Methods on a Low-Resource Language ... Edman, Lukas; Üstün, Ahmet; Toral, Antonio. - : arXiv, 2021 BASE Show details 2 On the Effectiveness of Dataset Embeddings in Mono-lingual,Multi-lingual and Zero-shot Conditions ... van der Goot, Rob; Üstün, Ahmet; Plank, Barbara. - : arXiv, 2021 BASE Show details 3 Multilingual Unsupervised Neural Machine Translation with Denoising Adapters ... Üstün, Ahmet; Bérard, Alexandre; Besacier, Laurent. - : arXiv, 2021 BASE Show details 4 Multilingual Unsupervised Neural Machine Translation with Denoising Adapters ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Berard, Alexandre; Besacier, Laurent. - : Underline Science Inc., 2021 BASE Show details 5 From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding ... van der Goot, Rob; Sharaf, Ibrahim; Imankulova, Aizhan. - : arXiv, 2021 BASE Show details 6 On the Difficulty of Translating Free-Order Case-Marking Languages ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bisazza, Arianna; Sportel, Stephan. - : Underline Science Inc., 2021 BASE Show details 7 UDapter: Language Adaptation for Truly Universal Dependency Parsing ... Üstün, Ahmet; Bisazza, Arianna; Bouma, Gosse. - : arXiv, 2020 BASE Show details 8 FiSSA at SemEval-2020 Task 9: Fine-tuned For Feelings ... Braaksma, Bertelt; Scholtens, Richard; van Suijlekom, Stan. - : arXiv, 2020 BASE Show details 9 Incorporating word embeddings in unsupervised morphological segmentation Üstün, Ahmet; Can, Burcu In: 2020 ; 1 ; 21 (2020) BASE Show details 10 Characters or morphemes: how to represent words? Üstün, Ahmet; Kurfalı, Murathan; Can, Burcu. - : Association for Computational Linguistics, 2018 BASE Show details 11 A Trie-Structured Bayesian Model for Unsupervised Morphological Segmentation ... Kurfalı, Murathan; Üstün, Ahmet; Can, Burcu. - : arXiv, 2017 BASE Show details 12 Turkish PoS Tagging by Reducing Sparsity with Morpheme Tags in Small Datasets ... Can, Burcu; Üstün, Ahmet; Kurfalı, Murathan. - : arXiv, 2017 Abstract: Sparsity is one of the major problems in natural language processing. The problem becomes even more severe in agglutinating languages that are highly prone to be inflected. We deal with sparsity in Turkish by adopting morphological features for part-of-speech tagging. We learn inflectional and derivational morpheme tags in Turkish by using conditional random fields (CRF) and we employ the morpheme tags in part-of-speech (PoS) tagging by using hidden Markov models (HMMs) to mitigate sparsity. Results show that using morpheme tags in PoS tagging helps alleviate the sparsity in emission probabilities. Our model outperforms other hidden Markov model based PoS tagging models for small training datasets in Turkish. We obtain an accuracy of 94.1% in morpheme tagging and 89.2% in PoS tagging on a 5K training dataset. ... : 13 pages, accepted and presented in 17th International Conference on Intelligent Text Processing and Computational Linguistics (CICLING) ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.1703.03200 https://arxiv.org/abs/1703.03200 BASE Hide details

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