Multilingual Query Translation With Word-Order Preservation
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Solution Overview
Problem
Existing systems struggle to accurately interpret multilingual queries due to differences in word order across languages, leading to misinterpretation and misunderstanding.
Innovation Solution
A method and system that translates multilingual queries word for word into a monolingual format, using natural language processing and a neural network trained on word order, to produce a natural language query in the destination language.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If word-for-word translation is applied to multilingual queries, then translation simplicity is improved, but word order accuracy deteriorates
Solution Approach 1:
The query processing is segmented into distinct stages: multilingual query reception, word-for-word translation to monolingual format, and natural language processing. This segmentation allows each stage to optimize independently, maintaining translation simplicity while achieving word order accuracy through the final NLP mapping stage.
Solution Approach 2:
A monolingual intermediate representation is introduced as a mediator between the multilingual query and the final natural language query. The multilingual query is first translated word-for-word to this monolingual intermediate form, which then undergoes NLP processing to produce the final output. This intermediary enables both simple translation and accurate word order handling.
2Adaptability or versatility
If multilingual queries are processed directly, then language support versatility is improved, but query interpretation accuracy deteriorates
Solution Approach 1:
The system provides universal language support by accepting queries in multiple source languages while maintaining a single destination language output. The word-for-word translation mechanism combined with NLP processing enables the system to handle diverse multilingual inputs uniformly, achieving both language versatility and interpretation accuracy.
Solution Approach 2:
The system changes the linguistic parameters of the query by translating from multiple source languages into a single destination language while preserving the original word order. This parameter transformation enables accurate interpretation by converting multilingual queries into a standardized monolingual format that the NLP system can process accurately.
3Stability of the object's composition
If word order is preserved in translation, then query structure fidelity is improved, but translation naturalness deteriorates
Solution Approach 1:
The word-for-word translation with preserved word order is performed as a preliminary action to create a monolingual intermediate representation. This preliminary translation maintains query structure fidelity, and the subsequent NLP processing step naturally adjusts the query to improve naturalness while preserving the original intent and structure.
Data Source
AI summary
Systems and methods for handling multilingual queries are provided. One example method includes receiving, at a computing device, an input, wherein the input comprises a multi-lingual query comprising at least a first source language and a second source language. The multi-lingual query is translated, word for word, into a destination language to produce a monolingual query, with the word order of the multilingual query and the word order of the monolingual query being the same. The monolingual query is processed using natural language processing to map the mono-lingual query to a natural language query in the destination language.