PREPOSITION ERROR CORRECTING METHOD AND DEVICE PERFORMING SAME

• US 20160180742A1
• Filed: 02/25/2014
• Published: 06/23/2016
• Est. Priority Date: 08/13/2013
• Status: Abandoned Application

• Current Assignee: Postech Academy-Industry Foundation
• Original Assignee: Postech Academy-Industry Foundation
• Inventors: LEE, Geun Bae, LEE, Kyu Song
• Application Number:
  US14/909,565
• Publication Number:
  US 20160180742A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 40/253 Grammatical analysis; Style critique
• CPC Class Codes: G06F 40/268 Morphological analysis
• CPC Class Codes: G09B 19/06 Foreign languages with audible presentation of material to be studied G09B5/04
• CPC Class Codes: G09B 5/06 with both visual and audible presentation of the material to be studied

Abstract

A method for correcting a preposition error and a device performing the same are provided. The method comprises the steps of normalizing input text by tagging the input text with part-of-speech information on words which form the input text; extracting a pattern indicating the structure of the input text on the basis of a preposition included in the nomalized input text; and correcting a preposition error included in the input text by matching an error pattern included in pre-constructed error pattern database and the extracted pattern. Therefore, the present invention can effectively correct a preposition error for a foreign language learner, and can precisely detect a preposition error of a foreign language learner, thereby enabling the foreign language learner to effectively learn grammar of a foreign language.

Claims

1. A method of correcting a preposition error, performed in an information processing apparatus capable of digital signal processing, the method comprising:

normalizing an input text by tagging words constituting the input text based on part-of-speech information of the words constituting the input text;

extracting at least one pattern indicating a structure of the input text based on a preposition included in the normalized input text; and

correcting a preposition error included in the input text by matching an error pattern included in a pre-constructed error pattern database and the extracted at least one pattern.

2. The method according to claim 1, wherein the error pattern database is constructed by verifying whether a preposition error exists or not through comparison between a pre-constructed grammatical error corpus and the at least one extracted error pattern, and recording the extracted at least one pattern in the error pattern database when it is determined that the preposition error exists in the input text.

3. The method according to claim 1, wherein the input text is normalized by substituting a word having temporal meaning in the tagged input text with time-type information based on a text dictionary.

4. The method according to claim 1, wherein the input text is normalized by substituting a word having a place implication in the tagged input text with place-type information based on named entity recognition.

5. The method according to claim 1, wherein the at least one pattern is extracted by extracting a plurality of word sequences by using words located prior to or subsequence to the preposition included in the normalized input text.

6. The method according to claim 5, wherein the preposition error is corrected by applying at least one of a probabilistic language model and a statistical language model to an error pattern matched to the error pattern database among the at least one extracted pattern.

7. A preposition error correcting apparatus, the apparatus comprising:

a text normalization part normalizing an input text by tagging words constituting the input text based on part-of-speech information of the words constituting the input text;

a pattern extraction part extracting at least one pattern indicating a structure of the input text based on a preposition included in the normalized input text; and

an error correction part correcting a preposition error included in the input text by matching an error pattern included in a pre-constructed error pattern database and the extracted at least one pattern.

8. The apparatus according to claim 7, wherein the error pattern database is constructed by verifying whether a preposition error exists or not through comparison between a pre-constructed grammatical error corpus and the extracted at least one error pattern, and recording the extracted at least one pattern in the error pattern database when it is determined that the preposition error exists in the input text.

9. The apparatus according to claim 7, wherein the text normalization part includes a time normalization module normalizing the input text by substituting a word having temporal meaning in the tagged input text with time-type information based on a text dictionary.

10. The apparatus according to claim 7, wherein the text normalization part includes a place normalization module substituting a word having a place implication in the tagged input text with place-type information based on named entity recognition.

11. The apparatus according to claim 7, wherein the pattern extraction part extracts the at least one pattern by extracting a plurality of word sequences by using words located prior to or subsequence to the preposition included in the normalized input text.

12. The apparatus according to claim 11, wherein the error correction part corrects the preposition error by applying at least one of a probabilistic language model and a statistical language model to an error pattern matched to the error pattern database among the at least one extracted patter