We present a program that recreates split compound errors with amusing effects in written Swedish. Two useful criteria for funniness is that the result should be grammatical and that the compound words should not be split into many short components.

We present a uniform framework for dealing with errors in natural language sentences within the context of :automated second language teaching. The idea is to use a feature grammar and to analyse errors as being sentences where features have other values than those they should have. By using a feature grammar it is possible to describe various types of errors (agreement, syntactic and semantic ...

This paper presents two classifications of errors in Czech texts. As a basic resource we use the corpus (Chyby – Errors) which has been continuously developed from 1999–2000 ([1]). The corpus text contains various kinds of errors such as spelling, typographical, grammatical, semantic, lexical, and stylistic ones. They have been corrected manually and annotated according to the classification of...

In this paper, we propose a new framework for online handwritten mathematical expression recognition. In this approach, we consider handwritten mathematical expressions as the output of stroke generation processes based on a stochastic context-free grammar which generates handwritten expressions stochastically. We estimate the most likely expression candidate derived from the grammar, rather th...

Since the Web by far represents the largest public repository of natural language texts, recent experiments, methods, and tools in the area of corpus linguistics often use the Web as a corpus. For applications where high accuracy is crucial, the problem has to be faced that a non-negligible number of orthographic and grammatical errors occur in Web documents. In this article we investigate the ...

This paper presents research on building a model of grammatical error correction, for preposition errors in particular, in English text produced by language learners. Unlike most previous work which trains a statistical classifier exclusively on well-formed text written by native speakers, we train a classifier on a large-scale, error-tagged corpus of English essays, relying on contextual and g...

We report the performance of a patient who, as a consequence of left frontal and temporoparietal strokes, makes far more errors on nouns than on verbs in spoken output tasks, but makes far more errors on verbs than on nouns in written input tasks. This double dissociation within a single patient with respect to grammatical category provides evidence for the hypothesis that phonological and orth...

Under one typical view, children’s acquisition of their L1 phonological grammar is understood as a gradual progression from an initial universal state towards a language-specific one, in which learners respond to mismatches between their outputs and the ambient language (i.e. their ‘errors’) by changing their grammars incrementally to better approximate the target (i.e. ‘resolving’ their errors...

Typical grammar checking software use some form of natural language parsing to determine if errors exist in the text. If a sentence is found ungrammatical, the grammar checker usually seeks a single grammatical error as an explanation. For non-native speakers of English, it is possible that a given sentence contain multiple errors and grammar checkers may not adequately explain these mistakes. ...