Search Results for author: Zoey Liu

Found 19 papers, 5 papers with code

A Predicate-Function-Argument Annotation of Natural Language for Open-Domain Information eXpression

no code implementations EMNLP 2020 Mingming Sun, Wenyue Hua, Zoey Liu, Xin Wang, Kangjie Zheng, Ping Li

Based on the same platform of OIX, the OIE strategies are reusable, and people can select a set of strategies to assemble their algorithm for a specific task so that the adaptability may be significantly increased.

Open Information Extraction Sentence

Dependency Parsing Evaluation for Low-resource Spontaneous Speech

1 code implementation EACL (AdaptNLP) 2021 Zoey Liu, Emily Prud’hommeaux

There is, however, much room for improvement on child utterances, particularly at 18 and 21 months, due to cases of omission and repetition that are prevalent in child speech.

Dependency Parsing

Enhancing Documentation of Hupa with Automatic Speech Recognition

no code implementations ComputEL (ACL) 2022 Zoey Liu, Justin Spence, Emily Tucker Prud’hommeaux

This study investigates applications of automatic speech recognition (ASR) techniques to Hupa, a critically endangered Native American language from the Dene (Athabaskan) language family.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Morphological Segmentation for Seneca

1 code implementation NAACL (AmericasNLP) 2021 Zoey Liu, Robert Jimerson, Emily Prud’hommeaux

This study takes up the task of low-resource morphological segmentation for Seneca, a critically endangered and morphologically complex Native American language primarily spoken in what is now New York State and Ontario.

Model Selection Multi-Task Learning +1

The Effect of Data Partitioning Strategy on Model Generalizability: A Case Study of Morphological Segmentation

no code implementations14 Apr 2024 Zoey Liu, Bonnie J. Dorr

Recent work to enhance data partitioning strategies for more realistic model evaluation face challenges in providing a clear optimal choice.

Morphological Inflection: A Reality Check

1 code implementation25 May 2023 Jordan Kodner, Sarah Payne, Salam Khalifa, Zoey Liu

Morphological inflection is a popular task in sub-word NLP with both practical and cognitive applications.

Morphological Inflection

Data-driven Parsing Evaluation for Child-Parent Interactions

1 code implementation28 Sep 2022 Zoey Liu, Emily Prud'hommeaux

We present a syntactic dependency treebank for naturalistic child and child-directed speech in English (MacWhinney, 2000).

Investigating data partitioning strategies for crosslinguistic low-resource ASR evaluation

no code implementations26 Aug 2022 Zoey Liu, Justin Spence, Emily Prud'hommeaux

Many automatic speech recognition (ASR) data sets include a single pre-defined test set consisting of one or more speakers whose speech never appears in the training set.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

UniMorph 4.0: Universal Morphology

no code implementations LREC 2022 Khuyagbaatar Batsuren, Omer Goldman, Salam Khalifa, Nizar Habash, Witold Kieraś, Gábor Bella, Brian Leonard, Garrett Nicolai, Kyle Gorman, Yustinus Ghanggo Ate, Maria Ryskina, Sabrina J. Mielke, Elena Budianskaya, Charbel El-Khaissi, Tiago Pimentel, Michael Gasser, William Lane, Mohit Raj, Matt Coler, Jaime Rafael Montoya Samame, Delio Siticonatzi Camaiteri, Benoît Sagot, Esaú Zumaeta Rojas, Didier López Francis, Arturo Oncevay, Juan López Bautista, Gema Celeste Silva Villegas, Lucas Torroba Hennigen, Adam Ek, David Guriel, Peter Dirix, Jean-Philippe Bernardy, Andrey Scherbakov, Aziyana Bayyr-ool, Antonios Anastasopoulos, Roberto Zariquiey, Karina Sheifer, Sofya Ganieva, Hilaria Cruz, Ritván Karahóǧa, Stella Markantonatou, George Pavlidis, Matvey Plugaryov, Elena Klyachko, Ali Salehi, Candy Angulo, Jatayu Baxi, Andrew Krizhanovsky, Natalia Krizhanovskaya, Elizabeth Salesky, Clara Vania, Sardana Ivanova, Jennifer White, Rowan Hall Maudslay, Josef Valvoda, Ran Zmigrod, Paula Czarnowska, Irene Nikkarinen, Aelita Salchak, Brijesh Bhatt, Christopher Straughn, Zoey Liu, Jonathan North Washington, Yuval Pinter, Duygu Ataman, Marcin Wolinski, Totok Suhardijanto, Anna Yablonskaya, Niklas Stoehr, Hossep Dolatian, Zahroh Nuriah, Shyam Ratan, Francis M. Tyers, Edoardo M. Ponti, Grant Aiton, Aryaman Arora, Richard J. Hatcher, Ritesh Kumar, Jeremiah Young, Daria Rodionova, Anastasia Yemelina, Taras Andrushko, Igor Marchenko, Polina Mashkovtseva, Alexandra Serova, Emily Prud'hommeaux, Maria Nepomniashchaya, Fausto Giunchiglia, Eleanor Chodroff, Mans Hulden, Miikka Silfverberg, Arya D. McCarthy, David Yarowsky, Ryan Cotterell, Reut Tsarfaty, Ekaterina Vylomova

The project comprises two major thrusts: a language-independent feature schema for rich morphological annotation and a type-level resource of annotated data in diverse languages realizing that schema.

Morphological Inflection

Not always about you: Prioritizing community needs when developing endangered language technology

no code implementations ACL 2022 Zoey Liu, Crystal Richardson, Richard Hatcher Jr, Emily Prud'hommeaux

Languages are classified as low-resource when they lack the quantity of data necessary for training statistical and machine learning tools and models.

Data-driven Model Generalizability in Crosslinguistic Low-resource Morphological Segmentation

1 code implementation5 Jan 2022 Zoey Liu, Emily Prud'hommeaux

Common designs of model evaluation typically focus on monolingual settings, where different models are compared according to their performance on a single data set that is assumed to be representative of all possible data for the task at hand.

Predicting pragmatic discourse features in the language of adults with autism spectrum disorder

no code implementations ACL 2021 Christine Yang, Duanchen Liu, Qingyun Yang, Zoey Liu, Emily Prud{'}hommeaux

Individuals with autism spectrum disorder (ASD) experience difficulties in social aspects of communication, but the linguistic characteristics associated with deficits in discourse and pragmatic expression are often difficult to precisely identify and quantify.

Informativeness

Predicting cross-linguistic adjective order with information gain

no code implementations Findings (ACL) 2021 William Dyer, Richard Futrell, Zoey Liu, Gregory Scontras

Languages vary in their placement of multiple adjectives before, after, or surrounding the noun, but they typically exhibit strong intra-language tendencies on the relative order of those adjectives (e. g., the preference for `big blue box' in English, `grande bo\^{i}te bleue' in French, and `alsund\={u}q al'azraq alkab\={\i}r' in Arabic).

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