Search Results for author: Ryo Nagata

Found 20 papers, 3 papers with code

Exploring Methods for Generating Feedback Comments for Writing Learning

1 code implementation EMNLP 2021 Kazuaki Hanawa, Ryo Nagata, Kentaro Inui

To shed light on these points, we investigate a wider range of methods for generating many feedback comments in this study.


Revisiting Statistical Laws of Semantic Shift in Romance Cognates

no code implementations COLING 2022 Yoshifumi Kawasaki, Maëlys Salingre, Marzena Karpinska, Hiroya Takamura, Ryo Nagata

This article revisits statistical relationships across Romance cognates between lexical semantic shift and six intra-linguistic variables, such as frequency and polysemy.

Word Embeddings

Taking the Correction Difficulty into Account in Grammatical Error Correction Evaluation

1 code implementation COLING 2020 Takumi Gotou, Ryo Nagata, Masato Mita, Kazuaki Hanawa

The performance measures are based on the simple idea that the more systems successfully correct an error, the easier it is considered to be.

Grammatical Error Correction

Creating Corpora for Research in Feedback Comment Generation

no code implementations LREC 2020 Ryo Nagata, Kentaro Inui, Shin{'}ichiro Ishikawa

In this paper, we report on datasets that we created for research in feedback comment generation {---} a task of automatically generating feedback comments such as a hint or an explanatory note for writing learning.

Toward a Task of Feedback Comment Generation for Writing Learning

no code implementations IJCNLP 2019 Ryo Nagata

We have tested three baseline methods on the dataset, showing that a simple neural retrieval-based method sets a baseline performance with an F-measure of 0. 34 to 0. 41.


Analytic Score Prediction and Justification Identification in Automated Short Answer Scoring

no code implementations WS 2019 Tomoya Mizumoto, Hiroki Ouchi, Yoriko Isobe, Paul Reisert, Ryo Nagata, Satoshi Sekine, Kentaro Inui

This paper provides an analytical assessment of student short answer responses with a view to potential benefits in pedagogical contexts.

A POS Tagging Model Adapted to Learner English

no code implementations WS 2018 Ryo Nagata, Tomoya Mizumoto, Yuta Kikuchi, Yoshifumi Kawasaki, Kotaro Funakoshi

Based on the discussion of possible causes of POS tagging errors in learner English, we show that deep neural models are particularly suitable for this.

Grammatical Error Correction Part-Of-Speech Tagging +1

Exploring the Influence of Spelling Errors on Lexical Variation Measures

no code implementations COLING 2018 Ryo Nagata, Taisei Sato, Hiroya Takamura

This paper introduces and examines the hypothesis that lexical richness measures become unstable in learner English because of spelling errors.

Analyzing the Impact of Spelling Errors on POS-Tagging and Chunking in Learner English

no code implementations WS 2017 Tomoya Mizumoto, Ryo Nagata

Part-of-speech (POS) tagging and chunking have been used in tasks targeting learner English; however, to the best our knowledge, few studies have evaluated their performance and no studies have revealed the causes of POS-tagging/chunking errors in detail.

Chunking Grammatical Error Correction +2

Analyzing Semantic Change in Japanese Loanwords

no code implementations EACL 2017 Hiroya Takamura, Ryo Nagata, Yoshifumi Kawasaki

We analyze semantic changes in loanwords from English that are used in Japanese (Japanese loanwords).

Word Embeddings

Discriminative Analysis of Linguistic Features for Typological Study

no code implementations LREC 2016 Hiroya Takamura, Ryo Nagata, Yoshifumi Kawasaki

We address the task of automatically estimating the missing values of linguistic features by making use of the fact that some linguistic features in typological databases are informative to each other.

Lensing reconstruction from a patchwork of polarization maps

1 code implementation26 May 2014 Toshiya Namikawa, Ryo Nagata

The lensing signals involved in CMB polarization maps have already been measured with ground-based experiments such as SPTpol and POLARBEAR, and would become important as a probe of cosmological and astrophysical issues in the near future.

Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics

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