AI Machine Translation Augments Document Summarization
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Solution Overview
Problem
In scenarios where a large corpus of documents in a specific language is not available to identify textual support for a statement, existing technologies face challenges in effectively extracting and verifying quotes across different languages.
Innovation Solution
The implementation of artificial intelligence-based machine translation to augment document summarization, where a quote is extracted from a document in one language and translated to another, allowing for the identification of supporting documents in both languages, thereby expanding the corpus of available documents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If machine translation is used to translate documents from one language to another, then the corpus size available for quote verification is increased, but the translation accuracy and reliability may be compromised
Solution Approach 1:
The patent uses machine translation as an intermediary tool to bridge language gaps, allowing documents in source language to be translated into target language for quote verification. This intermediary approach enables access to larger multilingual corpora while managing translation reliability through systematic verification processes.
Solution Approach 2:
The system implements feedback mechanisms where translation results are verified against the original quote and source documents. This feedback loop allows the system to assess translation quality and use it to improve future translations, thereby managing the reliability-quantity tradeoff.
2Reliability
If a larger corpus of documents in multiple languages is utilized, then the ability to identify supporting documents for a quote is improved, but the complexity of managing and processing multilingual data increases
Solution Approach 1:
The patent segments the quote verification process into distinct stages: quote extraction from target language documents, translation of the quote to source language, search for supporting documents in source language corpus, and verification of support. This segmentation manages complexity by breaking down the multilingual processing into manageable steps.
Solution Approach 2:
The system implements a universal quote verification mechanism that operates across multiple languages through machine translation. The same verification logic and search algorithms are applied regardless of the source or target language, making the system multi-functional and language-agnostic.
3Quantity of substance
If machine translation is applied to extract and verify quotes across languages, then the coverage of available supporting documents is expanded, but the time required for translation and verification increases
Solution Approach 1:
The system performs preliminary actions by pre-translating and indexing documents into multiple languages before quote verification is needed. This preliminary processing creates a ready-to-search multilingual corpus, reducing the time required for actual quote verification by eliminating the need for on-demand translation.
Data Source
AI summary
Technologies are disclosed for utilizing artificial intelligence-based machine translation to augment document summarization. Text can be extracted from a document in a first language. Machine translation can be utilized to translate the text from the first language to a second language. The translated text can be used to identify documents in the second language that include support for the translated text. A user interface can be provided that indicates the number of documents in the second language that provide support for the extracted text. Documents in the first language can also be translated to the second language. Documents that provide support for a text string can be identified in the documents translated to the second language and in other documents in the second language. A user interface can be provided that indicates the number of documents in the first language and the second language that provide support for the text.