Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Hulden, Mans"'
Autor:
Ginn, Michael, Hulden, Mans
Dynamic topic models have been proposed as a tool for historical analysis, but traditional approaches have had limited usefulness, being difficult to configure, interpret, and evaluate. In this work, we experiment with a recent approach for dynamic t
Externí odkaz:
http://arxiv.org/abs/2406.18907
Interlinear glossed text (IGT) is a popular format in language documentation projects, where each morpheme is labeled with a descriptive annotation. Automating the creation of interlinear glossed text would be desirable to reduce annotator effort and
Externí odkaz:
http://arxiv.org/abs/2406.18895
Publikováno v:
Transactions of the Association for Computational Linguistics, Vol 7, Pp 327-342 (2019)
We quantify the linguistic complexity of different languages’ morphological systems. We verify that there is a statistically significant empirical trade-off between paradigm size and irregularity: A language’s inflectional paradigms may be either
Externí odkaz:
https://doaj.org/article/0fb649718b164ce0bb10d522426035cb
Autor:
Muradoglu, Saliha, Hulden, Mans
Data scarcity is a widespread problem in numerous natural language processing (NLP) tasks for low-resource languages. Within morphology, the labour-intensive work of tagging/glossing data is a serious bottleneck for both NLP and language documentatio
Externí odkaz:
http://arxiv.org/abs/2210.14465
Autor:
Batsuren, Khuyagbaatar, Goldman, Omer, Khalifa, Salam, Habash, Nizar, Kieraś, Witold, Bella, Gábor, Leonard, Brian, Nicolai, Garrett, Gorman, Kyle, Ate, Yustinus Ghanggo, Ryskina, Maria, Mielke, Sabrina J., Budianskaya, Elena, El-Khaissi, Charbel, Pimentel, Tiago, Gasser, Michael, Lane, William, Raj, Mohit, Coler, Matt, Samame, Jaime Rafael Montoya, Camaiteri, Delio Siticonatzi, Sagot, Benoît, Rojas, Esaú Zumaeta, Francis, Didier López, Oncevay, Arturo, Bautista, Juan López, Villegas, Gema Celeste Silva, Hennigen, Lucas Torroba, Ek, Adam, Guriel, David, Dirix, Peter, Bernardy, Jean-Philippe, Scherbakov, Andrey, Bayyr-ool, Aziyana, Anastasopoulos, Antonios, Zariquiey, Roberto, Sheifer, Karina, Ganieva, Sofya, Cruz, Hilaria, Karahóǧa, Ritván, Markantonatou, Stella, Pavlidis, George, Plugaryov, Matvey, Klyachko, Elena, Salehi, Ali, Angulo, Candy, Baxi, Jatayu, Krizhanovsky, Andrew, Krizhanovskaya, Natalia, Salesky, Elizabeth, Vania, Clara, Ivanova, Sardana, White, Jennifer, Maudslay, Rowan Hall, Valvoda, Josef, Zmigrod, Ran, Czarnowska, Paula, Nikkarinen, Irene, Salchak, Aelita, Bhatt, Brijesh, Straughn, Christopher, Liu, Zoey, Washington, Jonathan North, Pinter, Yuval, Ataman, Duygu, Wolinski, Marcin, Suhardijanto, Totok, Yablonskaya, Anna, Stoehr, Niklas, Dolatian, Hossep, Nuriah, Zahroh, Ratan, Shyam, Tyers, Francis M., Ponti, Edoardo M., Aiton, Grant, Arora, Aryaman, Hatcher, Richard J., Kumar, Ritesh, Young, Jeremiah, Rodionova, Daria, Yemelina, Anastasia, Andrushko, Taras, Marchenko, Igor, Mashkovtseva, Polina, Serova, Alexandra, Prud'hommeaux, Emily, Nepomniashchaya, Maria, Giunchiglia, Fausto, Chodroff, Eleanor, Hulden, Mans, Silfverberg, Miikka, McCarthy, Arya D., Yarowsky, David, Cotterell, Ryan, Tsarfaty, Reut, Vylomova, Ekaterina
The Universal Morphology (UniMorph) project is a collaborative effort providing broad-coverage instantiated normalized morphological inflection tables for hundreds of diverse world languages. The project comprises two major thrusts: a language-indepe
Externí odkaz:
http://arxiv.org/abs/2205.03608
Autor:
Hulden, Mans, Bischoff, Shannon T.
Coyote Papers, Vol. 16 features a combined bibliography for all articles in the issue. This bibliography is available at http://arizona.openrepository.com/arizona/handle/10150/125965
This paper presents preliminary research on a computational pa
This paper presents preliminary research on a computational pa
Externí odkaz:
http://hdl.handle.net/10150/126389
Autor:
Liu, Ling, Hulden, Mans
Deep learning sequence models have been successfully applied to the task of morphological inflection. The results of the SIGMORPHON shared tasks in the past several years indicate that such models can perform well, but only if the training data cover
Externí odkaz:
http://arxiv.org/abs/2104.06483
Sequence-to-sequence models have delivered impressive results in word formation tasks such as morphological inflection, often learning to model subtle morphophonological details with limited training data. Despite the performance, the opacity of neur
Externí odkaz:
http://arxiv.org/abs/2104.00789
Autor:
Vylomova, Ekaterina, White, Jennifer, Salesky, Elizabeth, Mielke, Sabrina J., Wu, Shijie, Ponti, Edoardo, Maudslay, Rowan Hall, Zmigrod, Ran, Valvoda, Josef, Toldova, Svetlana, Tyers, Francis, Klyachko, Elena, Yegorov, Ilya, Krizhanovsky, Natalia, Czarnowska, Paula, Nikkarinen, Irene, Krizhanovsky, Andrew, Pimentel, Tiago, Hennigen, Lucas Torroba, Kirov, Christo, Nicolai, Garrett, Williams, Adina, Anastasopoulos, Antonios, Cruz, Hilaria, Chodroff, Eleanor, Cotterell, Ryan, Silfverberg, Miikka, Hulden, Mans
A broad goal in natural language processing (NLP) is to develop a system that has the capacity to process any natural language. Most systems, however, are developed using data from just one language such as English. The SIGMORPHON 2020 shared task on
Externí odkaz:
http://arxiv.org/abs/2006.11572
In this paper, we describe the findings of the SIGMORPHON 2020 shared task on unsupervised morphological paradigm completion (SIGMORPHON 2020 Task 2), a novel task in the field of inflectional morphology. Participants were asked to submit systems whi
Externí odkaz:
http://arxiv.org/abs/2005.13756