OcrV1, Main, Exploration, bibRecord, 000A67

Successfully detecting and correcting false friends using channel profiles

Identifieur interne : 000A67 ( Main/Exploration ); précédent : 000A66; suivant : 000A68

Successfully detecting and correcting false friends using channel profiles

Auteurs : Ulrich Reffle [Allemagne] ; Annette Gotscharek [Allemagne] ; Christoph Ringlstetter [Allemagne] ; Klaus U. Schulz [Allemagne]

Source :

International journal on document analysis and recognition : (Print) [ 1433-2833 ] ; 2009.

RBID : Pascal:10-0180628

Descripteurs français

Pascal (Inist)
- Texte, Reconnaissance caractère, Reconnaissance optique caractère, Dictionnaire, Correction automatique, Désambiguïsation, Analyse statistique, Approche probabiliste, Correction erreur, ..
Wicri :
- topic : Dictionnaire.

English descriptors

KwdEn :
- Automatic correction, Character recognition, Dictionaries, Disambiguation, Error correction, Optical character recognition, Probabilistic approach, Statistical analysis, Text.

Abstract

The detection and correction of false friends- also called real-word errors-is a notoriously difficult problem. On realistic data, the break-even point for automatic correction so far could not be reached: the number of additional infelicitous corrections outnumbered the useful corrections. We present a new approach where we first compute a profile of the error channel for the given text. During the correction process, the profile (1) helps to restrict attention to a small set of "suspicious" lexical tokens of the input text where it is "plausible" to assume that the token represents a false friend. In this way, recognition of false friends is improved. Furthermore, the profile (2) helps to isolate the "most promising" correction suggestion for "suspicious" tokens. Using a conventional word trigram statistics for disambiguation we obtain a correction method that can be successfully applied to unrestricted text. In experiments for OCR documents, we show significant accuracy gains by fully automatic correction of false friends.

Affiliations:

Links toward previous steps (curation, corpus...)

to stream PascalFrancis, to step Corpus: 000195
to stream PascalFrancis, to step Curation: 000582
to stream PascalFrancis, to step Checkpoint: 000182
to stream Main, to step Merge: 000A76
to stream Main, to step Curation: 000A67

Le document en format XML

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<front><div type="abstract" xml:lang="en">The detection and correction of false friends- also called real-word errors-is a notoriously difficult problem. On realistic data, the break-even point for automatic correction so far could not be reached: the number of additional infelicitous corrections outnumbered the useful corrections. We present a new approach where we first compute a profile of the error channel for the given text. During the correction process, the profile (1) helps to restrict attention to a small set of "suspicious" lexical tokens of the input text where it is "plausible" to assume that the token represents a false friend. In this way, recognition of false friends is improved. Furthermore, the profile (2) helps to isolate the "most promising" correction suggestion for "suspicious" tokens. Using a conventional word trigram statistics for disambiguation we obtain a correction method that can be successfully applied to unrestricted text. In experiments for OCR documents, we show significant accuracy gains by fully automatic correction of false friends.</div>
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Successfully detecting and correcting false friends using channel profiles

Successfully detecting and correcting false friends using channel profiles

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri