APPARATUS FOR PROVIDING FEEDBACK OF TRANSLATION QUALITY USING CONCEPT-BSED BACK TRANSLATION

• US 20100274552A1
• Filed: 08/09/2006
• Published: 10/28/2010
• Est. Priority Date: 08/09/2006
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Gu, Liang, Zhou, Bowen, Gao, Yuqing, Kuo, Hong-Kwang
• Granted Patent: US 7,848,915 B2
• Time in Patent Office: Days
• US Class Current: 704/2
• CPC Class Codes: G06F 40/51 Translation evaluation

Abstract

A concept-based back translation system includes a target language semantic parser module, a source language semantic parser module, a bi-directional machine translation module, a relevancy judging module, and a back translation display module.

Claims

1. (canceled)

2. (canceled)

3. A concept-based back translation system, comprising:

a target language semantic parser module, which uses statistical techniques including decision trees to train a parser based on annotated corpus in the target language, parses a translated target sentence with the parser, once it has been trained, to extract semantic concepts, and based on results of parsing the translated target sentence, obtains a backward translation of the translated sentence into a source language;

a source language semantic parser module, which parses a source language sentence to extract semantic concepts and uses results of parsing the source language sentence to determine a significance and relevance of the extract concepts generated in the target language sentence;

a bi-directional machine translation module, which receives a translated target language sentence and converts the translated target language sentence back into the source language;

a relevancy judging module, which measures a significance and a relevance of the back translation by semantically comparing the back translation with an original source language sentence; and

a back translation display module, which displays the back translation dynamically based on the relevance and the significance of the back translation

wherein the relevancy judging module measures the relevancy using a semantically weighted score based on modified n-gram precision where the original source language sentence is treated as a reference, and the back translation is treated as a translation hypothesis,

wherein the relevancy between the hypothesis and the reference are compared based on a modified n-gram precision, which automatically evaluates translation performance, and

wherein a higher weight is assigned to n-grams that contain significant semantic annotations, and a lower weight is assigned to n-grams that contain no significant semantic role, the significance of the n-grams is judged based on semantic parsing results, and on a predefined list of key concepts for an application domain.

4. The concept-based translation system according to claim 3, wherein the back translation display module, assigns appropriate confidence scores to the concepts in the back translation,

wherein the confidence scores are obtained as a combination of parsing confidence of source language, target language, a significance score of a corresponding concept in the application domain, and relevance judge score obtained from the relevancy judging module.