Title:
RECOGNITION ERROR CORRECTION DEVICE AND CORRECTION MODEL
Document Type and Number:
WIPO Patent Application WO/2020/225999
Kind Code:
A1
Abstract:
The present invention addresses the problem of building an environment in which a process for correcting a recognition error in a recognition result for voice recognition or character recognition is presented. A recognition error correction device 1 is provided with: a pair data acquisition unit 21 that acquires pair data in which a sentence, of recognition results for voice recognition or character recognition, and a label string, configured from a process label which is a label indicating a process for correcting a recognition error regarding each word constituting the sentence, are associated; and a correction model generation unit 22 that implements machine learning by using the pair data acquired by the pair data acquisition unit 21 to thereby generate a correction model, which is a learned model for correcting a recognition error of the recognition results. The recognition error correction device 1 is further provided with a pair data creation unit 20 that creates pair data on the basis of a comparison between a sentence of a recognition result and correct answer data for the recognition result, and the pair data acquisition unit 21 may acquire pair data created by the pair data creation unit 20.
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Inventors:
IKEDA TAISHI (JP)
Application Number:
PCT/JP2020/014584
Publication Date:
November 12, 2020
Filing Date:
March 30, 2020
Export Citation:
Assignee:
NTT DOCOMO INC (JP)
International Classes:
G06K9/03; G06N20/00; G10L15/22
Foreign References:
| JPH0214000A | 1990-01-18 | |||
| JP2011197410A | 2011-10-06 | |||
| JP2014044363A | 2014-03-13 |
Other References:
SAWAI, YUICHIRO ET AL.: "Usage of the unlabeled corpus by pseudo error generation for grammatical error correction", PROCEEDINGS OF THE 23RD ANNUAL MEETING OF THE ASSOCIATION FOR NATURAL LANGUAGE PROCESSING, 6 March 2017 (2017-03-06), pages 714 - 717
IKEDA, TAISHI ET AL.: "Neural Sequence-Labelling Models for ASR Error Correction", THE 33RD ANNUAL CONFERENCE OF THE JAPANESE SOCIETY FOR ARTIFICIAL INTELLIGENCE, 4 June 2019 (2019-06-04)
IKEDA, TAISHI ET AL.: "Neural Sequence-Labelling Models for ASR Error Correction", THE 33RD ANNUAL CONFERENCE OF THE JAPANESE SOCIETY FOR ARTIFICIAL INTELLIGENCE, 4 June 2019 (2019-06-04)
Attorney, Agent or Firm:
HASEGAWA Yoshiki et al. (JP)
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