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Learning Exceptionality And Variation With Lexically Scaled Maxent, Coral Hughto, Andrew Lamont, Brandon Prickett, Gaja Jarosz 2019 University of Massachusetts, Amherst

Learning Exceptionality And Variation With Lexically Scaled Maxent, Coral Hughto, Andrew Lamont, Brandon Prickett, Gaja Jarosz

Proceedings of the Society for Computation in Linguistics

A growing body of research in phonology addresses the representation and learning of variable processes and exceptional, lexically conditioned processes. Linzen et al. (2013) present a MaxEnt model with additive lexical scales to account for data exhibiting both variation and exceptionality. In this paper, we implement a learning model for lexically scaled MaxEnt grammars which we show to be successful across a range of data containing patterns of variation and exceptionality. We also explore how the model's parameters and the rate of exceptionality in the data influence its performance and predictions for novel forms.


Learning Phonotactic Restrictions On Multiple Tiers, Kevin McMullin, Alëna Aksënova, Aniello De Santo 2019 University of Ottawa

Learning Phonotactic Restrictions On Multiple Tiers, Kevin Mcmullin, Alëna Aksënova, Aniello De Santo

Proceedings of the Society for Computation in Linguistics

No abstract provided.


Evaluating Domain-General Learning Of Parametric Stress Typology, Gaja Jarosz, Aleksei Nazarov 2019 University of Massachusetts Amherst

Evaluating Domain-General Learning Of Parametric Stress Typology, Gaja Jarosz, Aleksei Nazarov

Proceedings of the Society for Computation in Linguistics

No abstract provided.


Exploring Transit-Based Environmental Injustices In San Gabriel Valley And Greater Los Angeles, Bailey Lai 2019 Claremont Colleges

Exploring Transit-Based Environmental Injustices In San Gabriel Valley And Greater Los Angeles, Bailey Lai

Pomona Senior Theses

This thesis attempts to disentangle the multilayered interactions between Greater Los Angeles’s history, its built environment, and its inequitable treatment of different peoples, focusing on how transportation in surrounding suburban communities like San Gabriel Valley has developed in relation to the inner city of Los Angeles. Greater Los Angeles contains a long, winding trajectory of transit-based environmental injustices, from the indigenous societies being overtaken by the Spanish missions, to the railroads and streetcars boosting the farmlands and urban growth of Los Angeles, leading into the decline of transit and rise of automobile-oriented suburbia. Within the San Gabriel Valley, the ...


Preface: Scil 2019 Editors’ Note, Gaja Jarosz, Max Nelson, Brendan O'Connor, Joe Pater 2019 University of Massachusetts Amherst

Preface: Scil 2019 Editors’ Note, Gaja Jarosz, Max Nelson, Brendan O'Connor, Joe Pater

Proceedings of the Society for Computation in Linguistics

No abstract provided.


A Brief History Of Digital Preservation, Erin Baucom 2019 University of Montana, Missoula

A Brief History Of Digital Preservation, Erin Baucom

Mansfield Library Faculty Publications

Digital objects are composed of bitstreams, sequences of 1’s and 0’s, which require specific software (and in some cases hardware) to make the content understandable to human users. Digital objects, like word processing documents, digital images, websites, e-mails, datasets and so much more, are fragile, easy to modify, and susceptible to bit rot (loss or reordering parts of the bitstream) and obsolescence. Digital preservation is a combination of policies and workflows that dictate the active management of digital objects to ensure their continued authenticity and meaningful access over time. Obsolescence is one of the unending battles that digital ...


Gender, Adverse Family-Of-Origin Experiences, And Current, Nichole M. Kuck 2019 Wright State University

Gender, Adverse Family-Of-Origin Experiences, And Current, Nichole M. Kuck

Browse all Theses and Dissertations

Prior research has determined that there is a trend within the military that military women experience more relationship disruption than military men and no conclusive findings as to why this may occur. There has been preliminary research indicating that military women experience more Adverse Childhood Experiences (ACE)s than military men. Civilian research has shown definitive findings that there are long-term physical, emotional, and relational consequences of ACEs. This purpose of this study was to determine if an adverse family-of-origin environment characterized by traumatic events and a conflictual and less cohesive family-of-origin environment impacted current relationship functioning as a possible ...


Unsupervised Learning Of Cross-Lingual Symbol Embeddings Without Parallel Data, Mark Granroth-Wilding, Hannu Toivonen 2019 University of Helsinki

Unsupervised Learning Of Cross-Lingual Symbol Embeddings Without Parallel Data, Mark Granroth-Wilding, Hannu Toivonen

Proceedings of the Society for Computation in Linguistics

We present a new method for unsupervised learning of multilingual symbol (e.g. character) embeddings, without any parallel data or prior knowledge about correspondences between languages. It is able to exploit similarities across languages between the distributions over symbols' contexts of use within their language, even in the absence of any symbols in common to the two languages. In experiments with an artificially corrupted text corpus, we show that the method can retrieve character correspondences obscured by noise. We then present encouraging results of applying the method to real linguistic data, including for low-resourced languages. The learned representations open the ...


Modeling The Acquisition Of Words With Multiple Meanings, Libby Barak, Sammy Floyd, Adele Goldberg 2019 Princeton University

Modeling The Acquisition Of Words With Multiple Meanings, Libby Barak, Sammy Floyd, Adele Goldberg

Proceedings of the Society for Computation in Linguistics

Learning vocabulary is essential to successful communication. Complicating this task is the underappreciated fact that most common words are associated with multiple senses (are polysemous) (e.g., baseball cap vs. cap of a bottle), while other words are homonymous, evoking meanings that are unrelated to one another (e.g., baseball bat vs. flying bat). Models of human word learning have thus far failed to represent this level of naturalistic complexity. We extend a feature-based computational model to allow for multiple meanings, while capturing the gradient distinction between polysemy and homonymy by using structured sets of features. Results confirm that the ...


Evaluation Order Effects In Dynamic Continuized Ccg: From Negative Polarity Items To Balanced Punctuation, Michael White 2019 The Ohio State University

Evaluation Order Effects In Dynamic Continuized Ccg: From Negative Polarity Items To Balanced Punctuation, Michael White

Proceedings of the Society for Computation in Linguistics

Combinatory Categorial Grammar's (CCG; Steedman, 2000) flexible

treatment of word order and constituency enable it to employ a compact

lexicon, an important factor in its successful application to a range

of NLP problems. However, its word order flexibility can be

problematic for linguistic phenomena where linear order plays a key

role. In this paper, we show that the enhanced control over

evaluation order afforded by Continuized CCG (Barker & Shan, 2014)

makes it possible to not only implement an improved analysis of

negative polarity items in Dynamic Continuized CCG (White et al.,

2017) but also to develop an accurate treatment ...


Abstract Meaning Representation For Human-Robot Dialogue, Claire N. Bonial, Lucia Donatelli, Jessica Ervin, Clare R. Voss 2019 U.S. Army Research Lab

Abstract Meaning Representation For Human-Robot Dialogue, Claire N. Bonial, Lucia Donatelli, Jessica Ervin, Clare R. Voss

Proceedings of the Society for Computation in Linguistics

In this research, we begin to tackle the

challenge of natural language understanding

(NLU) in the context of the development of

a robot dialogue system. We explore the adequacy

of Abstract Meaning Representation

(AMR) as a conduit for NLU. First, we consider

the feasibility of using existing AMR

parsers for automatically creating meaning

representations for robot-directed transcribed

speech data. We evaluate the quality of output

of two parsers on this data against a manually

annotated gold-standard data set. Second,

we evaluate the semantic coverage and distinctions

made in AMR overall: how well does it

capture the meaning and distinctions needed ...


Augmentic Compositional Models For Knowledge Base Completion Using Gradient Representations, Matthias R. Lalisse, Paul Smolensky 2019 Johns Hopkins University

Augmentic Compositional Models For Knowledge Base Completion Using Gradient Representations, Matthias R. Lalisse, Paul Smolensky

Proceedings of the Society for Computation in Linguistics

Neural models of Knowledge Base data have typically employed compositional representations of graph objects: entity and relation embeddings are systematically combined to evaluate the truth of a candidate Knowedge Base entry. Using a model inspired by Harmonic Grammar, we propose to tokenize triplet embeddings by subjecting them to a process of optimization with respect to learned well-formedness conditions on Knowledge Base triplets. The resulting model, known as Gradient Graphs, leads to sizable improvements when implemented as a companion to compositional models. Also, we show that the "supracompositional" triplet token embeddings it produces have interpretable properties that prove helpful in performing ...


On Evaluating The Generalization Of Lstm Models In Formal Languages, Mirac Suzgun, Yonatan Belinkov, Stuart M. Shieber 2019 Harvard University

On Evaluating The Generalization Of Lstm Models In Formal Languages, Mirac Suzgun, Yonatan Belinkov, Stuart M. Shieber

Proceedings of the Society for Computation in Linguistics

Recurrent Neural Networks (RNNs) are theoretically Turing-complete and established themselves as a dominant model for language processing. Yet, there still remains an uncertainty regarding their language learning capabilities. In this paper, we empirically evaluate the inductive learning capabilities of Long Short-Term Memory networks, a popular extension of simple RNNs, to learn simple formal languages, in particular anbn, anbncn, and anbncndn. We investigate the influence of various aspects of learning, such as training data regimes and model capacity, on the generalization to unobserved samples. We find ...


Empty Categories Help Parse The Overt, Weiwei Sun 2019 Peking University

Empty Categories Help Parse The Overt, Weiwei Sun

Proceedings of the Society for Computation in Linguistics

This paper is concerned with whether deep syntactic information can help surface parsing, with a particular focus on empty categories. We consider data-driven dependency parsing with both linear and neural disambiguation models. We find that the information about empty categories is helpful to reduce the approximation error in a structured prediction based parsing model, but increases the search space for inference and accordingly the estimation error. To deal with structure-based overfitting, we propose to integrate disambiguation models with and without empty elements. Experiments on English and Chinese TreeBanks indicate that incorporating empty elements consistently improves surface parsing.


Temporally-Oriented Possession: A Corpus For Tracking Possession Over Time, Dhivya I. Chinnappa, Alexis Palmer, Eduardo Blanco 2019 University of North Texas

Temporally-Oriented Possession: A Corpus For Tracking Possession Over Time, Dhivya I. Chinnappa, Alexis Palmer, Eduardo Blanco

Proceedings of the Society for Computation in Linguistics

This abstract presents a new corpus for temporally-oriented possession or tracking concrete objects as they change hands over time. We annotate Wikipedia articles for 90 different well-known artifacts (paintings, diamonds, and archaeological artifacts), producing 799 artifact-possessor relations covering 735 unique possessors. Each possession relation is annotated with features capturing duration of possession, as well as the certainty of the possession according to textual evidence. A possession timeline is then produced for each artifact. This corpus provides a foundation for analysis of temporally-oriented possession, as well as work on automatic production of possession timelines.


Rnn Classification Of English Vowels: Nasalized Or Not, Ling Liu, Mans Hulden, Rebecca Scarborough 2019 University of Colorado Boulder

Rnn Classification Of English Vowels: Nasalized Or Not, Ling Liu, Mans Hulden, Rebecca Scarborough

Proceedings of the Society for Computation in Linguistics

Vowel nasality is perceived and used by English listeners though it is not phonemic. Feature-based classifiers have been built to evaluate what features are useful for nasality perception and measurement. These classifiers require heavy high-level feature engineering with most features discrete and measured at discrete points. Recurrent neural networks can take advantage of sequential information, and has the advantage of freeing us from high-level feature engineering and potentially being stronger simulation models with a holistic view. Therefore, we constructed two types of RNN classifiers (vanilla RNN and LSTM) with MFCCs of the vowel as input to predict whether the vowel ...


Developing A Real-Time Translator From Neural Signals To Text: An Articulatory Phonetics Approach, Lindy Comstock, Ariel Tankus, Michelle Tran, Nader Pouratian, Itzhak Fried, William Speier 2019 University of California, Los Angeles

Developing A Real-Time Translator From Neural Signals To Text: An Articulatory Phonetics Approach, Lindy Comstock, Ariel Tankus, Michelle Tran, Nader Pouratian, Itzhak Fried, William Speier

Proceedings of the Society for Computation in Linguistics

New developments in brain-computer interfaces (BCI) harness machine learning to decode spoken language from electrocorticographic (ECoG) and local field potential (LFP) signals. Orienting to signals associated with motor movements that produce articulatory features improves phoneme detection quality: individual phonemes share features, but possess a unique feature set; classification by feature set allows for a finer distinction between neural signals. Data indicates vowels are more detectable, consonants have greater detection accuracy, place of articulation informs precision, and manner of articulation affects recall. Findings have implications for the multisensory integration of speech and the role of motor imagery in phonemic neural representations.


On The Interaction Between Dependency Frequency And Semantic Fit In Sentence Processing, Soo Hyun Ryu, Rui P. Chaves 2019 University at Buffalo

On The Interaction Between Dependency Frequency And Semantic Fit In Sentence Processing, Soo Hyun Ryu, Rui P. Chaves

Proceedings of the Society for Computation in Linguistics

No abstract provided.


Finding Law, Stephen E. Sachs 2019 Duke Law School

Finding Law, Stephen E. Sachs

Faculty Scholarship

That the judge's task is to find the law, not to make it, was once a commonplace of our legal culture. Today, decades after Erie, the idea of a common law discovered by judges is commonly dismissed -- as a "fallacy," an "illusion," a "brooding omnipresence in the sky." That dismissive view is wrong. Expecting judges to find unwritten law is no childish fiction of the benighted past, but a real and plausible option for a modern legal system.

This Essay seeks to restore the respectability of finding law, in part by responding to two criticisms made by Erie and ...


The Information-Fluent English Language Learner: Cultural And Pedagogical Considerations, Megan Hodge 2019 Virginia Commonwealth University

The Information-Fluent English Language Learner: Cultural And Pedagogical Considerations, Megan Hodge

VCU Libraries Faculty and Staff Publications

No abstract provided.


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