Virtual Translator Avatars for Language Translation in Virtual Applications
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Solution Overview
Problem
In virtual universes, users from diverse linguistic backgrounds face communication barriers due to the lack of translators for all languages and dialects, and traditional machine translation methods struggle with idioms and abbreviated speech, leading to inaccurate translations.
Innovation Solution
A method and system for language translation in virtual applications that determine user languages, find optimal translator sequences, and teleport translator avatars to a virtual meeting location, utilizing a network of connected translators, including human and machine translators, to facilitate real-time communication across language barriers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional machine translation methods are used, then translation speed is maintained, but translation accuracy deteriorates due to inability to handle idioms and abbreviated speech
Solution Approach 1:
The translation task is segmented into multiple stages: initial machine translation, detection of problematic segments (idioms, abbreviations), human translator intervention for specific segments, and reassembly. This segmentation allows machine handling of straightforward content while human experts handle complex linguistic elements, improving overall accuracy without requiring full human review of all content.
Solution Approach 2:
The system introduces an intermediary layer that identifies and flags difficult translation segments (idioms, abbreviated speech) for human translator attention. This intermediary mechanism selectively routes only problematic content to human translators, maintaining efficiency while improving accuracy for challenging linguistic elements.
2Adaptability or versatility
If translators are added for all language pairs, then communication coverage is improved, but system complexity increases
Solution Approach 1:
The system uses intermediate languages as mediators for translation between language pairs where direct translators don't exist. Instead of requiring direct translator connections for all language pairs, the system routes translations through intermediate languages that have established translator connections, reducing the total number of required translators while maintaining comprehensive language pair coverage.
Solution Approach 2:
Translators for intermediate languages serve multiple functions: they translate between their native language and the intermediate language, and also facilitate translation between various other language pairs through the intermediate language. This multi-functionality reduces the total number of translators needed while expanding language pair coverage.
3Measurement precision
If human translators are used for all communications, then translation accuracy is improved, but communication speed decreases
Solution Approach 1:
The translation process is segmented so that machine translation handles the majority of content rapidly, while human translators only process identified problematic segments. This segmentation maintains high overall communication speed while ensuring accurate translation of difficult linguistic elements through selective human intervention.
Solution Approach 2:
Instead of applying full human translation to all content, the system applies partial human translation only to the extent necessary for problematic segments. This partial action approach maintains communication speed while providing human-level accuracy where most needed.
4Ease of operation
If direct translation between user and correspondent is attempted, then communication simplicity is maintained, but communication feasibility deteriorates when no direct translator exists
Solution Approach 1:
The system automatically introduces intermediate language translators as mediators when direct translation is unavailable, transparently handling the complexity of multi-step translation chains. Users experience simple direct communication interfaces while the system reliably routes messages through appropriate intermediate translators in the background.
Data Source
AI summary
Methods and apparatus for language translation in a computing environment associated with a virtual application are presented. For example, a method for providing language translation includes determining languages of a user and a correspondent; determining one or more sequences of translators; determining a selected sequence of selected translators from the one or more sequences of the translators; requesting a change in virtual locations, within the computing environment associated with the virtual application, of one or more selected translator virtual representations of the selected translators to a virtual meeting location within the computing environment associated with the virtual application; and changing virtual locations of the one or more selected translator virtual representations to the virtual meeting location. One or more of determining languages, determining one or more sequences, determining a selected sequence, requesting a change in virtual locations, and changing virtual locations occur on a processor device.