Robert Joshua Reynolds

Brigham Young University, UiT–The Arctic University of Norway
0000-0003-0306-087X
https://reynoldsnlp.com/
Publications11
h-index5
Citations48
Highly Influential Citations5
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Insights from Russian second language readability classification: complexity-dependent training requirements, and feature evaluation of multiple categories
TLDR
Investigation of Russian second language readability assessment using a machine-learning approach with a range of lexical, morphological, syntactic, and discourse features shows that morphological features are collectively the most informative. Expand
Russian natural language processing for computer-assisted language learning: Capturing the benefits of deep morphological analysis in real-life applications
xvii Acknowledgements xix
A VIEW of Russian: Visual Input Enhancement and Adaptive Feedback
TLDR
It is shown that the same information and techniques used for target selection can often be repurposed for adaptive feedback, and Authentic Text ICALL systems incorporating only native-language NLP, without the NLP analysis specific to learner language that is characteristic of Intelligent Language Tutoring Systems (ILTS), thus can support some forms of adaptive feedback. Expand
Automatic word stress annotation of Russian unrestricted text
TLDR
The effectiveness of finitestate tools for automatically annotating word stress in Russian unrestricted text is evaluated, highlighting the need for morphosyntactic disambiguation in the word stress placement task for Russian, and setting a standard for future research on this task. Expand
A preliminary constraint grammar for Russian
TLDR
This paper presents preliminary work on a constraint grammar based disambiguator for Russian that is tuned to be high recall (over 0.99) at the expense of low precision. Expand
Who needs particles? A challenge to the classification of particles as a part of speech in Russian
TLDR
This work proposes a reclassification of Russian particles that implements Zwicky’s directive and provides a detailed account of various sub-uses that correspond to different parts of speech, their relationships, and relative distribution. Expand
A Bayesian Investigation of Factors Shaping the Network Structure of Inflection Class Systems
Construal vs. redundancy: Russian aspect in context
Abstract The relationship between construal and redundancy has not been previously explored empirically. Russian aspect allows speakers to construe situations as either Perfective or Imperfective,… Expand
The Most Likely Steady State for Large Numbers of Stochastic Traveling Salesmen
Disk Scheduling in System V
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