Pre-translated Parallel Sentence Retrieval for Translation Accuracy
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Solution Overview
Problem
Conventional machine translation methods face challenges in providing accurate and clear example sentences in both source and target languages, leading to user confusion due to the computational intensity of translating sentences back into the source language.
Innovation Solution
A method and system that utilize a database of parallel sentences in both languages to retrieve and display example sentences native to the target language, reducing the risk of unclear or incorrect translations by ranking sentences based on relevance and popularity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If example sentences are translated back into the source language using a translation algorithm, then the user can see corresponding sentences in both languages, but the computational cost increases and there is a risk of providing unclear or incorrect translation
Solution Approach 1:
The patent pre-translates example sentences from the source language to the target language before the user query, storing both versions in advance. This eliminates the need for real-time back-translation during user interaction, reducing computational cost and avoiding potential translation errors while maintaining reliability.
2Use of energy by moving object
If example sentences are provided in the target language only, then the computational cost is reduced, but the user may have difficulty understanding the context in their source language
Solution Approach 1:
The system pre-translates and stores example sentences in both source and target languages, allowing it to retrieve ready-made bilingual pairs without performing real-time translation. This maintains ease of operation by providing contextually accurate examples in both languages while avoiding the computational overhead of on-demand translation.
3Adaptability or versatility
If multiple translation algorithms are used to generate different target phrases, then the semantic coverage is improved, but the device complexity increases
Solution Approach 1:
The patent generates multiple target phrases using different translation algorithms during the offline preparation phase, storing these pre-computed translations along with their corresponding example sentences. During online operation, the system simply retrieves the appropriate pre-computed phrases based on the user query, maintaining semantic coverage while avoiding the complexity of running multiple algorithms in real-time.
Data Source
AI summary
There is disclosed a method and system for translating a source phrase in a first language into a second language. The method being executable by a device configured to access an index comprising a set of source sentences in the first language, and a set of target sentences in the second language, each of the target sentence corresponding to a translation of a given source sentence. The method comprises: acquiring the source phrase; generating by a translation algorithm, one or more target phrases, each of the one or more target phrases having a different semantic meaning within the second language; retrieving, from the index, a respective target sentence for each of the one or more target phrases, the respective target sentence comprising one of the one or more target phrases; and selecting each of the one or more target phrase and the respective target sentences for display.