The present paper proposes automatic error analysis methods that use patterns representing grammatical check points. Our method is comparable to or slightly outperforms conventional methods for automatic evaluation metrics. Different from the conventional methods, our method enables error analysis for each grammatical check point. While our method does not depend on languages, we experimentally...

We focus on two leading state-of-the-art approaches to grammatical error correction – machine learning classification and machine translation. Based on the comparative study of the two learning frameworks and through error analysis of the output of the state-of-the-art systems, we identify key strengths and weaknesses of each of these approaches and demonstrate their complementarity. In particu...

Many evaluation issues for grammatical error detection have previously been overlooked, making it hard to draw meaningful comparisons between different approaches, even when they are evaluated on the same corpus. To begin with, the three-way contingency between a writer’s sentence, the annotator’s correction, and the system’s output makes evaluation more complex than in some other NLP tasks, wh...

ABSTRACTA language is a communication tool used by every human being in everyday life. People their to communicate with each other help deliver the information. Meanwhile, Indonesians lack grammar, especially studying from unreliable sources, such as listening songs. This research trying analyze grammatical error Justin Bieber’s song lyrics and identify most frequent type of errors found lyrics...

Even with high overall parsing accuracy, datadriven parsers often make errors in the assignment of core grammatical functions such as subject and object. Starting from a detailed error analysis of a state-of-the-art dependency parser for Swedish, we show that the addition of linguistically motivated features targeting specific error types may lead to substantial improvements, both for specific ...

We present a study of the impact of morphological and syntactic ambiguity in the process of grammatical error detection. We will present three different systems that have been devised with the objective of detecting grammatical errors in Basque and will examine the influence of ambiguity in their results. We infer that the ambiguity rate in the input to an error detection tool can have a consid...

State-of-the-art systems for grammatical error correction are based on a collection of independently-trained models for specific errors. Such models ignore linguistic interactions at the sentence level and thus do poorly on mistakes that involve grammatical dependencies among several words. In this paper, we identify linguistic structures with interacting grammatical properties and propose to a...

Research on grammatical error correction has received considerable attention. For dealing with all types of errors, grammatical error correction methods that employ statistical machine translation (SMT) have been proposed in recent years. An SMT system generates candidates with scores for all candidates and selects the sentence with the highest score as the correction result. However, the 1-bes...

The problem of finding quantum-error-correcting codes is transformed into the problem of finding additive codes over the field GF (4) which are self-orthogonal with respect to a certain trace inner product. Many new codes and new bounds are presented, as well as a table of upper and lower bounds on such codes of length up to 30 qubits.