Real-Time Video Chat Translation with Progressive Word Display
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Solution Overview
Problem
During video calls, users speaking different languages face challenges in understanding each other due to language barriers, leading to a less-than-ideal user experience.
Innovation Solution
A language translation method and device that continuously receives and translates voice data in real-time, displaying second-language words simultaneously with voice reproduction, using a combination of voice recognition, translation servers, and databases to provide immediate translations of spoken sentences and their fragments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If real-time translation is implemented during video calls, then language communication capability is improved, but system complexity increases due to integration of voice recognition, translation servers, and databases
Solution Approach 1:
The translation system is divided into separate functional modules: voice recognition module, translation module, and display module. Each module handles a specific task independently, allowing the system to manage complexity through functional segmentation while maintaining real-time translation capability across different languages.
Solution Approach 2:
A server acts as an intermediary between the client device and translation database. The server handles the complex tasks of voice recognition processing and translation lookup, while the client device focuses on receiving and displaying results. This mediation reduces the complexity burden on individual components.
2Ease of operation
If continuous real-time translation is provided, then user experience smoothness is improved, but processing time increases due to continuous voice data analysis and translation
Solution Approach 1:
Translation phrases and sentences are pre-loaded into the database during system initialization. When voice data is received, the system performs pattern matching against these pre-prepared translations rather than generating translations from scratch, significantly reducing processing time while maintaining continuous translation capability.
Solution Approach 2:
The system processes voice data in periodic segments rather than attempting to analyze entire conversations continuously. It identifies speech boundaries and processes translations at discrete intervals, which reduces computational overhead while maintaining the perception of continuous translation for the user.
3Speed
If immediate translation display is implemented, then reactivity is improved, but translation accuracy may deteriorate due to processing incomplete or fragmented sentences
Solution Approach 1:
The system displays translations progressively as voice data accumulates. It shows partial translations for incomplete sentences and updates them when complete sentences are detected, rather than waiting for full sentence confirmation before displaying any translation. This approach maintains reactivity while gradually improving accuracy as more context becomes available.
Solution Approach 2:
The system continuously monitors incoming voice data and adjusts translation display based on sentence completion detection. When a complete sentence is identified, the system provides feedback by updating the translation display with the accurate complete sentence translation, correcting any previously displayed partial translations.
Data Source
AI summary
A method of providing real-time translation for video chat is provided. The method includes: continuously receiving first-language voice data and at least one second-language word from a first terminal; continuously displaying the at least one second-language word at the same time as reproduction of the voice data; acquiring a second-language translation of an ended sentence included in a voice recognition result for the voice data; and substituting at least one word, which corresponds to the ended sentence in the displayed at least one second-language word, with the acquired translation. The at least one second-language word corresponds to respective words included in the voice recognition result for the voice data.