Multistage Multimedia Translation Using an Intermediate Language

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Solution Overview

Problem

Conventional techniques for automated translation of digital multimedia fail to accurately interpret and translate diverse content across multiple languages, leading to inefficient and resource-intensive processes.

Innovation Solution

A natural language generation system that receives a search request, determines a response in a first natural language, reconfigures it through intermediate languages based on lexical similarity, and translates it to a preferred natural language using multiple translation subsystems, optimizing the process for seamless language conversion.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional automated translation techniques are used for digital multimedia, then translation capability is provided, but accuracy in interpreting and translating diverse content across multiple languages deteriorates

Engineering Contradiction:

Improvetranslation accuracyVSAvoidmulti-language content handling

Core Design Contradiction:

Measurement precisionVSAdaptability or versatility

Solution Approach 1:

The translation system is segmented into multiple specialized translation subsystems, each trained for specific language pairs or content types. This allows the system to handle diverse multilingual content with high accuracy by routing different content to appropriate subsystems rather than using a single general-purpose translator.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system introduces an intermediary language model that acts as a mediator between source and target languages. This intermediary layer enables more accurate translation of diverse content by providing a standardized intermediate representation that captures semantic meaning before final translation, improving accuracy across multiple language pairs.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If multiple translation subsystems with intermediate languages are used, then translation accuracy improves, but system complexity increases

Engineering Contradiction:

Improvetranslation accuracyVSAvoidtranslation system structure

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The intermediate language model serves multiple functions: it acts as a bridge between different language pairs, provides semantic normalization, and enables consistent translation quality across all subsystems. This multi-functionality justifies the added complexity by providing centralized control and improved accuracy.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system performs preliminary translation to the intermediate language before final target language translation. This two-stage approach allows for better quality control and consistency, as the intermediate representation standardizes the input for final translation subsystems.

Inventive Principle:

Principle #10Preliminary action

3Productivity

If conventional translation processes are used, then processing speed is maintained, but resource efficiency deteriorates due to manual input and redundant steps

Engineering Contradiction:

Improveprocessing efficiencyVSAvoidcomputing resource consumption

Core Design Contradiction:

ProductivityVSLoss of energy

Solution Approach 1:

The translation system is fully automated with no manual input required. The system self-manages the entire translation pipeline including content analysis, subsystem selection, intermediate language conversion, and output generation. This eliminates manual intervention overhead and optimizes resource usage through automated decision-making.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system extracts and removes redundant processing steps from conventional translation workflows. By directly processing digital multimedia content through automated subsystems without manual intermediation, the system eliminates wasteful steps and reduces computing resource consumption while maintaining productivity.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS20250356138A1Natural language generation system for automated translation of digital multimedia

Publication Date: 2025.11.20 BANK OF AMERICA CORP

AI summary

Systems, computer program products, and methods are described herein for automated translation of digital multimedia. The present disclosure is configured to receive, from a user input device, a search request; determine the response for the search query in a first natural language, wherein the response comprises digital multimedia; reconfigure the response for display on the user input device in the preferred natural language, wherein reconfiguring further comprises: determining an intermediate natural language based on a lexical similarity with the preferred natural language; translating, using a first natural language translation subsystem, the response from the first natural language to the intermediate language; and translating, using a second natural language translation subsystem, the response from the intermediate language to the preferred natural language; and display the reconfigured response on the user input device in the preferred natural language.