Olga Zamaraeva


2020

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A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization
Graham Neubig | Shruti Rijhwani | Alexis Palmer | Jordan MacKenzie | Hilaria Cruz | Xinjian Li | Matthew Lee | Aditi Chaudhary | Luke Gessler | Steven Abney | Shirley Anugrah Hayati | Antonios Anastasopoulos | Olga Zamaraeva | Emily Prud’hommeaux | Jennette Child | Sara Child | Rebecca Knowles | Sarah Moeller | Jeffrey Micher | Yiyuan Li | Sydney Zink | Mengzhou Xia | Roshan S Sharma | Patrick Littell
Proceedings of the 1st Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL)

Despite recent advances in natural language processing and other language technology, the application of such technology to language documentation and conservation has been limited. In August 2019, a workshop was held at Carnegie Mellon University in Pittsburgh, PA, USA to attempt to bring together language community members, documentary linguists, and technologists to discuss how to bridge this gap and create prototypes of novel and practical language revitalization technologies. The workshop focused on developing technologies to aid language documentation and revitalization in four areas: 1) spoken language (speech transcription, phone to orthography decoding, text-to-speech and text-speech forced alignment), 2) dictionary extraction and management, 3) search tools for corpora, and 4) social media (language learning bots and social media analysis). This paper reports the results of this workshop, including issues discussed, and various conceived and implemented technologies for nine languages: Arapaho, Cayuga, Inuktitut, Irish Gaelic, Kidaw’ida, Kwak’wala, Ojibwe, San Juan Quiahije Chatino, and Seneca.

2019

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Modeling Clausal Complementation for a Grammar Engineering Resource
Olga Zamaraeva | Kristen Howell | Emily M. Bender
Proceedings of the Society for Computation in Linguistics (SCiL) 2019

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Handling cross-cutting properties in automatic inference of lexical classes: A case study of Chintang
Olga Zamaraeva | Kristen Howell | Emily M. Bender Handling cross-cutting properties in automatic inference of lexical classes: A case study of Chintang
Proceedings of the 3rd Workshop on the Use of Computational Methods in the Study of Endangered Languages Volume 1 (Papers)

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Visualizing Inferred Morphotactic Systems
Haley Lepp | Olga Zamaraeva | Emily M. Bender
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations)

We present a web-based system that facilitates the exploration of complex morphological patterns found in morphologically very rich languages. The need for better understanding of such patterns is urgent for linguistics and important for cross-linguistically applicable natural language processing. In this paper we give an overview of the system architecture and describe a sample case study on Abui [abz], a Trans-New Guinea language spoken in Indonesia.

2018

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Clausal Modifiers in the Grammar Matrix
Kristen Howell | Olga Zamaraeva
Proceedings of the 27th International Conference on Computational Linguistics

We extend the coverage of an existing grammar customization system to clausal modifiers, also referred to as adverbial clauses. We present an analysis, taking a typologically-driven approach to account for this phenomenon across the world’s languages, which we implement in the Grammar Matrix customization system (Bender et al., 2002, 2010). Testing our analysis on testsuites from five genetically and geographically diverse languages that were not considered in development, we achieve 88.4% coverage and 1.5% overgeneration.

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Improving Feature Extraction for Pathology Reports with Precise Negation Scope Detection
Olga Zamaraeva | Kristen Howell | Adam Rhine
Proceedings of the 27th International Conference on Computational Linguistics

We use a broad coverage, linguistically precise English Resource Grammar (ERG) to detect negation scope in sentences taken from pathology reports. We show that incorporating this information in feature extraction has a positive effect on classification of the reports with respect to cancer laterality compared with NegEx, a commonly used tool for negation detection. We analyze the differences between NegEx and ERG results on our dataset and how these differences indicate some directions for future work.

2017

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Inferring Case Systems from IGT: Enriching the Enrichment
Kristen Howell | Emily M. Bender | Michel Lockwood | Fei Xia | Olga Zamaraeva
Proceedings of the 2nd Workshop on the Use of Computational Methods in the Study of Endangered Languages

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Computational Support for Finding Word Classes: A Case Study of Abui
Olga Zamaraeva | František Kratochvíl | Emily M. Bender | Fei Xia | Kristen Howell
Proceedings of the 2nd Workshop on the Use of Computational Methods in the Study of Endangered Languages

2016

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Inferring Morphotactics from Interlinear Glossed Text: Combining Clustering and Precision Grammars
Olga Zamaraeva
Proceedings of the 14th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology