Location-Based Candidate Language Subsets for Translation Apps

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Solution Overview

Problem

Existing translation applications require users to manually scroll through multiple languages to select the correct language for translation, which is time-consuming and resource-intensive, often leading to erroneous selections and unnecessary computational waste.

Innovation Solution

A system that narrows the selection of candidate languages based on the user's location and device features, rendering a subset of languages for selection, and uses targeted language identification models to accurately determine the spoken language.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If all available languages are rendered for user selection, then language selection completeness is improved, but user interface complexity and selection time increase

Engineering Contradiction:

Improvelanguage selection completenessVSAvoiduser interface complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent segments the complete language list into a subset of candidate languages based on location data. Instead of presenting all available languages, the system divides and selects only those languages relevant to the user's geographic location, reducing interface complexity while maintaining completeness for the relevant context.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system changes the parameter of language selection from a static complete list to a dynamic subset based on location parameters. By using location data as a filtering parameter, the system adapts the language list to the user's geographic context, reducing the number of options presented while ensuring the correct language is available.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If multiple language identification models are run for all languages, then language identification accuracy is improved, but computational resource consumption increases

Engineering Contradiction:

Improvelanguage identification accuracyVSAvoidcomputational resource consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The patent extracts and runs language identification models only for the subset of candidate languages relevant to the user's location, rather than executing models for all available languages. This extraction principle reduces computational resource consumption by eliminating unnecessary model executions while maintaining accuracy for the languages that matter.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system performs partial action by running language identification models for only some languages (the location-based subset) rather than all languages. This partial execution of the language identification process reduces computational overhead while still achieving accurate language detection for the relevant languages.

Inventive Principle:

Principle #16Partial or excessive action

3Measurement precision

If users manually scroll through all languages to select the correct language, then language selection accuracy is improved, but time consumption increases

Engineering Contradiction:

Improvelanguage selection accuracyVSAvoidlanguage selection time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary action by pre-filtering the language list based on location data before presenting options to the user. This preliminary filtering reduces the number of languages the user needs to scroll through, significantly reducing selection time while maintaining accuracy by ensuring the correct language is included in the reduced set.

Inventive Principle:

Principle #10Preliminary action

4Adaptability or versatility

If the complete language list is processed, then translation coverage is improved, but processing time and computational load increase

Engineering Contradiction:

Improvetranslation coverageVSAvoidtranslation processing efficiency

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The patent segments the complete language set into a location-based subset, processing only the relevant languages for translation operations. This segmentation maintains translation coverage for the user's context while dramatically improving processing efficiency by eliminating unnecessary language processing.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system changes the processing scope from all languages to a location-parameter-based subset. By using geographic location as a filtering parameter, the system optimizes translation processing efficiency while maintaining adequate coverage for the user's regional context.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250238639A1Generating subset(s) of candidate languages for translation application(s)

Publication Date: 2025.07.24 GOOGLE LLC

AI summary

Various implementations include initiating, at a client device, a translation application for translation of a dialog session between a first user speaking in a first language and a second user speaking in a second language. In many implementations, the first language, spoken by the first user, can be determined based on one or more features of the client device. Additional or alternative implementations include determining a subset of candidate second languages from a plurality of languages available to the translation application. In a variety of implementations, the system can render output based on the subset of candidate second languages, and can process received input from the second user indicative of one or more of the candidate second languages in the subset of candidate second languages.