Translation System Paraphrase Matching Syntax Coincidence
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Solution Overview
Problem
Existing translation techniques face challenges in improving translation reliability without enhancing the knowledge space, particularly when input sentences have phrasing beyond the scope of the available knowledge data, and enhancing this space is costly and ineffective.
Innovation Solution
A method that generates and evaluates paraphrased sentences based on predetermined rules, calculating degrees of coincidence in syntax and textual similarity to extract relevant translation references from a database, allowing for reliable translation results without extensive knowledge space expansion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the knowledge space in the translation device is enhanced to improve translation reliability, then translation reliability is improved, but device complexity and cost increase
Solution Approach 1:
The patent introduces an intermediary process between the input sentence and translation output: generating multiple paraphrased versions of the input sentence, calculating syntax coincidence degrees against database sentences, and selecting the best match. This intermediary mechanism enables reliable translation without requiring the device to store extensive knowledge data, thus resolving the contradiction between translation reliability and knowledge space complexity
Solution Approach 2:
The patent performs preliminary actions by generating multiple paraphrased sentences before actual translation matching occurs. By pre-generating variant forms of the input sentence and pre-calculating their syntax coincidence degrees against the database, the system prepares multiple candidates in advance, improving translation reliability without requiring the device to maintain a large knowledge space
2Reliability
If more knowledge data is stored in the translation device to cover diverse phrasings, then translation reliability is improved, but loss of time for data storage and processing increases
Solution Approach 1:
The patent extracts only the essential syntactic structure from sentences in the database rather than storing and processing complete semantic knowledge. By calculating syntax coincidence degrees based on extracted structural features rather than comprehensive knowledge matching, the system reduces data processing time while maintaining translation reliability across diverse phrasings
3Reliability
If the translation device uses exact matching with database sentences, then translation reliability is improved, but adaptability to new phrasings deteriorates
Solution Approach 1:
The patent segments the translation matching process into multiple independent components: generating multiple paraphrased versions of the input sentence, calculating syntax coincidence degrees for each version against database sentences, and selecting the best match. This segmentation allows the system to handle diverse phrasings adaptably while maintaining reliability through systematic evaluation of multiple candidates
Solution Approach 2:
The patent introduces dynamic flexibility into the translation process by allowing the system to adaptively generate and evaluate multiple paraphrased sentences based on the input. Rather than using fixed exact matching rules, the system dynamically adjusts by calculating syntax coincidence degrees and selecting from multiple candidates, enabling both reliability and adaptability to new phrasings
Data Source
AI summary
A method for providing a translation, including: acquiring a first sentence in a first language via a user terminal; determining whether the first sentence is in a database including sentences in the first language and corresponding translations in a second language; if the first sentence is not in the database, generating second sentences by replacing one or more words in the first sentence, based on a predetermined rule; calculating respective degrees of coincidence for syntax between the second sentences and sentences in the first language included in the database; extracting third sentences in the first language which are included in the database and for which the calculated degree of coincidence is at least a threshold value; and displaying fourth sentences in the second language which are corresponding translations for the third sentences in the database, on the user terminal as corresponding translation references for the first sentence.