Natural Language Generation for Intermediate-Language Multimedia Translation
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Solution Overview
Problem
Conventional techniques for automated translation of digital multimedia struggle to accurately interpret and translate diverse content across multiple languages, leading to inefficiencies and resource wastage.
Innovation Solution
A natural language generation system that receives a search request, determines a response in a first natural language, identifies an intermediate language based on lexical similarity, and translates the response through multiple subsystems to a preferred natural language, optimizing the translation process and conserving resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional translation techniques are used for digital multimedia, then translation coverage is achieved, but translation accuracy deteriorates
Solution Approach 1:
The patent segments the translation process into multiple specialized subsystems: speech-to-text translation subsystem, text-to-text translation subsystem, and text-to-speech translation subsystem. Each subsystem handles specific types of multimedia content with dedicated translation methods, improving accuracy for each segment while maintaining comprehensive coverage across all multimedia types.
Solution Approach 2:
The patent introduces an intermediate language representation layer between the source and target languages. The translation process converts source content to an intermediate semantic representation first, then to the target language, preserving meaning and improving translation accuracy across different language pairs while maintaining versatility.
2Productivity
If direct translation from source to target language is performed, then translation speed is improved, but translation quality deteriorates
Solution Approach 1:
The system uses an intermediate semantic representation as a mediator in the translation process. Content is first converted to this intermediate form which captures the essential meaning, then translated to the target language. This approach maintains translation quality by preserving semantic information while enabling efficient processing through the standardized intermediate representation.
Solution Approach 2:
The patent performs preliminary processing of source content into a standardized intermediate representation before translation. This pre-processing step organizes and structures the content in a way that facilitates faster and more accurate translation, improving both quality and speed by preparing the data in advance.
3Adaptability or versatility
If comprehensive translation subsystems are implemented for all languages, then translation versatility is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal intermediate representation that serves multiple translation functions. This single intermediate form can represent various types of content (speech, text, video) and can be translated to any target language, providing versatility without requiring separate complex subsystems for each language pair.
Solution Approach 2:
The system segments translation functionality into modular subsystems (speech-to-text, text-to-text, text-to-speech) that can be independently selected and combined. This modular architecture provides comprehensive translation versatility while keeping each individual subsystem relatively simple and manageable.
4Measurement precision
If manual translation processes are used, then translation accuracy is improved, but resource consumption increases
Solution Approach 1:
The patent implements automated translation subsystems that process multimedia content independently without requiring manual intervention. The system self-manages the translation process from source to target language through intelligent algorithms, maintaining high accuracy while eliminating the resource consumption associated with manual translation processes.
Solution Approach 2:
The system replaces manual mechanical translation processes with automated computational translation subsystems. These electronic systems process and translate content efficiently using algorithms and processing power, achieving accuracy comparable to or better than manual translation while consuming fewer human resources and reducing overall resource consumption.
Data Source
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.