Microsoft technology licensing, llc (20240185003). REPRESENTATION LEARNING OF CROSS-LANGUAGE TEXTS simplified abstract
REPRESENTATION LEARNING OF CROSS-LANGUAGE TEXTS
Organization Name
microsoft technology licensing, llc
Inventor(s)
Zhijie Sang of Redmond WA (US)
Xingyao Zhang of Redmond WA (US)
REPRESENTATION LEARNING OF CROSS-LANGUAGE TEXTS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240185003 titled 'REPRESENTATION LEARNING OF CROSS-LANGUAGE TEXTS
Simplified Explanation
The patent application describes a method and apparatus for learning representations of texts in different languages. It involves generating joint representations of source and target language texts, identifying relations among words in the texts, and projecting the joint representation to a target language representation.
- Representation learning of cross-language texts
- Generating joint representations of source and target language texts
- Identifying relations among words in the texts
- Projecting joint representation to target language representation
Potential Applications
This technology can be used in machine translation systems, cross-lingual information retrieval, and multilingual sentiment analysis.
Problems Solved
This technology addresses the challenge of effectively representing and translating texts across different languages.
Benefits
The technology improves the accuracy and efficiency of cross-language text representation and translation, enhancing communication and understanding across language barriers.
Commercial Applications
- Multilingual communication platforms
- Language learning tools
- Global business communication software
Prior Art
There are existing methods for cross-language text representation and translation, but this patent application introduces a novel approach to learning representations of texts in different languages.
Frequently Updated Research
Research on cross-language text representation and translation is ongoing, with advancements in neural network models and natural language processing techniques.
Questions about Representation Learning of Cross-Language Texts
Question 1
How does this technology improve upon existing methods of cross-language text representation and translation?
This technology enhances the accuracy and efficiency of representing and translating texts in different languages by generating joint representations and identifying relations among words.
Question 2
What are the potential implications of this technology for multilingual communication in global business settings?
This technology can streamline communication processes in multinational companies, improve cross-cultural collaboration, and facilitate international business transactions.
Original Abstract Submitted
the present disclosure proposes a method and apparatus for representation learning of cross-language texts. a source language text and a target language text may be obtained. an initial joint representation of the source language text and the target language text may be generated. relations among a plurality of words in the source language text and the target language text may be identified. a joint representation of the source language text and the target language text may be generated based on the initial joint representation and the relations. the joint representation may be projected to at least a target language representation corresponding to the target language text.