Search Results for author: Michael Flor

Found 25 papers, 1 papers with code

Automatic Generation of Distractors for Fill-in-the-Blank Exercises with Round-Trip Neural Machine Translation

no code implementations ACL 2022 Subhadarshi Panda, Frank Palma Gomez, Michael Flor, Alla Rozovskaya

In a fill-in-the-blank exercise, a student is presented with a carrier sentence with one word hidden, and a multiple-choice list that includes the correct answer and several inappropriate options, called distractors.

Machine Translation Multiple-choice +2

Lexical concreteness in narrative

no code implementations WS 2019 Michael Flor, Swapna Somasundaran

This study explores the relation between lexical concreteness and narrative text quality.

Relation

How to account for mispellings: Quantifying the benefit of character representations in neural content scoring models

no code implementations WS 2019 Brian Riordan, Michael Flor, Robert Pugh

Character-based representations in neural models have been claimed to be a tool to overcome spelling variation in in word token-based input.

Spelling Correction

A Corpus of Non-Native Written English Annotated for Metaphor

no code implementations NAACL 2018 Beata Beigman Klebanov, Chee Wee (Ben) Leong, Michael Flor

We present a corpus of 240 argumentative essays written by non-native speakers of English annotated for metaphor.

A Semantic Role-based Approach to Open-Domain Automatic Question Generation

no code implementations WS 2018 Michael Flor, Brian Riordan

We present a novel rule-based system for automatic generation of factual questions from sentences, using semantic role labeling (SRL) as the main form of text analysis.

Dependency Parsing Question Generation +3

Catching Idiomatic Expressions in EFL Essays

no code implementations WS 2018 Michael Flor, Beata Beigman Klebanov

The study used a corpus of essays written during a standardized examination of English language proficiency.

Sentiment Analysis and Lexical Cohesion for the Story Cloze Task

no code implementations WS 2017 Michael Flor, Swapna Somasundaran

Our lexical cohesion system achieves accuracy comparable to previously published baseline results.

Sentiment Analysis

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