AI Translation Apparatus Using Candidate Term Confidence and Language Probability
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current translation methods using artificial intelligence are inflexible and lack accuracy, often requiring user modifications to achieve desired syntactical structures and may lose intended content, failing to meet user requirements.
Innovation Solution
A method and apparatus that utilize a trained translation model and language model to determine candidate terms and their confidences, predict language probabilities, and recommend target terms for accurate translation, ensuring flexible and accurate translation by combining source and target language terms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If whole sentence translation is used, then translation speed is improved, but translation accuracy deteriorates
Solution Approach 1:
The patent segments the translation process into multiple stages: first translating individual words or phrases to obtain candidate translations, then selecting the most appropriate candidates based on confidence scores and contextual analysis. This segmentation allows both efficient processing and high accuracy by handling translation at appropriate granularities.
Solution Approach 2:
The patent introduces an intermediary selection mechanism that evaluates multiple candidate translations and selects the best fit based on confidence scores, contextual relevance, and linguistic rules. This intermediary layer bridges the gap between rapid machine translation and accurate human-like translation.
2Productivity
If rigid translation structure is used, then processing efficiency is improved, but flexibility deteriorates
Solution Approach 1:
The patent implements a dynamic translation system that adapts its structure based on the specific translation task. The system can adjust between more rigid processing for straightforward translations and more flexible candidate evaluation for complex or ambiguous cases, optimizing both efficiency and adaptability.
Solution Approach 2:
The patent changes parameters such as confidence thresholds and candidate selection criteria based on the complexity and context of the translation task. This allows the system to maintain high processing efficiency for simple translations while providing flexibility and accuracy for complex translations.
3Measurement precision
If user modification is required, then translation accuracy is improved, but operation complexity deteriorates
Solution Approach 1:
The patent implements a self-service translation system that automatically selects the most appropriate translation from multiple candidates based on confidence scores and contextual analysis. This eliminates the need for user modification in most cases, maintaining high accuracy while simplifying operation.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system learns from user interactions and automatically improves its translation selections. The system uses confidence scores and selection history to refine future translations, reducing the need for manual intervention while maintaining or improving accuracy.
Data Source
AI summary
The resent disclosure provides a method and an apparatus for translating based on artificial intelligence. With the method, the text to be translated from the source language to the target language is acquired, in which, the text includes the target language term and the source language term. The candidate terms for translating the source language term and confidences of the candidate terms are determined. The candidate terms are used to replace the corresponding source language term, and each candidate term is combined with the target language term, so as to obtain each candidate translation. A probability of forming a smooth text when the candidate term is used in the candidate translation is predicted. Then the target term is chosen to be recommended according to the language probabilities of the candidate translations and the confidences of the candidate terms.