Translation Device Using Common Language Intermediary
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Solution Overview
Problem
Conventional translation devices require frequent and cumbersome language setting changes when multiple languages are involved in a conversation, leading to increased resource consumption and memory utilization.
Innovation Solution
A translation method and device that converts conversational voice into a general language content, allowing any language to be translated into a common format and then outputted in any target language, using a set of encoders and decoders specific to each language, reducing resource consumption and improving memory utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional translation devices use one-to-one translation between different languages, then translation accuracy is maintained, but device complexity and resource consumption increase significantly
Solution Approach 1:
The patent introduces a common language as an intermediary medium between different source and target languages. Instead of requiring direct translator pairs for every language combination, the system translates source languages into the common language first, then from the common language to target languages. This mediator approach reduces the number of translators needed from N*(N-1) to N+M where N is the number of source languages and M is the number of target languages.
Solution Approach 2:
The translation process is segmented into two distinct stages: encoding from source languages to common language, and decoding from common language to target languages. This segmentation allows the system to reuse the common language representation across multiple translation tasks, reducing overall computational resources and device complexity while maintaining translation quality.
2Adaptability or versatility
If translation devices support multiple language pairs, then adaptability improves, but memory utilization and resource consumption increase
Solution Approach 1:
The common language serves as a universal intermediate representation that can be used for translating between any pair of source and target languages. Each translator only needs to implement translation to/from the common language, making the system universally applicable to any language combination without requiring separate translator pairs for each language pair, thus reducing memory utilization while maintaining multi-lingual adaptability.
3Adaptability or versatility
If users need to switch between different language settings, then translation flexibility is maintained, but ease of operation deteriorates
Solution Approach 1:
The system automatically detects the source language and selects the appropriate translator to convert it to the common language, then automatically selects the translator to convert from the common language to the target language. This self-service mechanism eliminates the need for users to manually configure language settings or select specific translator pairs, improving ease of operation while maintaining the flexibility to handle multiple language combinations.
Data Source
AI summary
A translation method includes steps of providing a translation device, inputting a first conversational voice corresponded to a first language, converting the first conversational voice into a general language content, converting the general language content into a second conversational voice corresponded to a second language, and outputting the second conversational voice. As a result, any language may be translated into a general language, and then translated into any target language, so that the advantages of implementing multi-lingual translations and conversations with simple setting are achieved.