Unified Language Model for Multi-Language Lexicon Construction
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Solution Overview
Problem
Current language modeling approaches, such as the bag-of-words model, are inefficient when dealing with multiple languages as they require separate models for each language, leading to inefficiencies and overhead.
Innovation Solution
A unified language model is developed that focuses on commonalities within and between languages, allowing for the representation of multiple languages in a single lexicon by parsing text into content words and elements, classifying them based on commonality, and performing statistical analysis to define entries that include root words, usage patterns, and plural forms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate language models are used for each language, then language-specific accuracy is maintained, but system complexity and processing overhead increase
Solution Approach 1:
The patent merges multiple language-specific models into a single unified language model that processes multiple languages simultaneously. The unified model consolidates vocabulary, grammar rules, and statistical parameters from individual language models into one integrated system, reducing overall system complexity while maintaining the ability to handle language-specific nuances through a shared processing framework.
Solution Approach 2:
The unified language model achieves multi-functionality by designing a single model architecture that can process and analyze multiple languages. The model uses universal linguistic features and cross-lingual patterns to handle different languages, allowing one model to perform the functions previously requiring separate models for each language, thereby reducing system complexity.
2Measurement precision
If separate language models are used for each language, then language-specific processing accuracy is maintained, but processing efficiency decreases
Solution Approach 1:
By merging multiple language processing tasks into a single unified model, the system achieves economies of scale in processing. The unified model shares computational resources, memory structures, and processing pathways across languages, reducing redundant computations and improving overall processing efficiency compared to running separate models for each language.
Solution Approach 2:
The unified language model performs preliminary learning of cross-lingual patterns and shared linguistic structures during training, which accelerates subsequent processing of multiple languages. By pre-establishing universal language representations and relationships, the model reduces the computational burden during actual processing, thereby improving efficiency while maintaining accuracy.
3Adaptability or versatility
If multiple separate models are maintained, then comprehensive language coverage is achieved, but resource overhead increases
Solution Approach 1:
The unified language model achieves universal language coverage by incorporating vocabulary, grammatical structures, and statistical parameters from multiple languages into a single model. This multi-functional design allows the model to handle diverse languages without requiring separate model instances, thereby reducing memory usage, storage requirements, and computational overhead while maintaining comprehensive language support.
Solution Approach 2:
The unified model uses parameter sharing and adaptation mechanisms where linguistic parameters are dynamically adjusted based on the input language while maintaining a shared core representation. This allows the model to cover multiple languages by changing parameters rather than maintaining separate complete models, significantly reducing resource overhead while preserving language-specific accuracy.
Data Source
AI summary
Embodiments of the invention provide systems and methods for representing a plurality of languages in a lexicon based on a unified language model. More specifically, embodiments of the present invention utilize a language model that focuses on commonalities within a particular language and between languages. Such commonalities may be based on rhyming of the words, other patterns within the words, and more generally, prosody of the words, phrases, and/or language overall. Prosody is commonly defined as the rhythm, stress, and intonation of the language when spoken. Using a language model defining such characteristics for one or more languages, embodiments of the present invention can define a lexicon for those one or more languages. In this lexicon, words and phrases of the one or more languages can be represented and classified into groups based on the commonalities between them.