Real-Time Automated Language Translation System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current automated language translation systems in electronic communications, such as conference calls and video conferences, introduce delays and unnatural pauses due to the need for participants to manually control translation, disrupting the spontaneity of real-time communication.
Innovation Solution
The system automatically translates speech in real-time or near real-time without requiring participants to activate or deactivate translation controls, allowing seamless language interpretation across multiple languages during communication sessions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated language translation systems use manual control buttons for participants to activate translation, then translation accuracy and control are improved, but communication spontaneity and real-time flow are worsened
Solution Approach 1:
The system automatically detects when translation should be activated by monitoring audio streams for speaker identification and language detection, eliminating the need for manual button presses. The translation system serves itself by autonomously determining when to start and stop translating based on the conversation flow, thereby maintaining both accuracy and spontaneity.
Solution Approach 2:
The system continuously monitors the audio stream to detect when a speaker finishes speaking and pauses, using this feedback to automatically activate translation. The system adjusts translation timing based on real-time detection of speech patterns, ensuring translations occur at optimal moments without disrupting the natural flow of conversation.
2Measurement precision
If the translation system waits for participants to release control buttons after speaking, then translation timing precision is improved, but communication naturalness and real-time feel are worsened
Solution Approach 1:
The system performs preliminary detection of speech patterns and speaker identification before translation is needed. By continuously analyzing audio streams and detecting when speakers pause or finish speaking, the system prepares translation activation in advance, ensuring precise timing without requiring manual control releases.
Solution Approach 2:
The system replaces the mechanical button-control mechanism with automated audio-based detection. Instead of relying on participants physically pressing and releasing buttons, the system uses audio processing to detect speech patterns, speaker changes, and pauses, automatically triggering translation at the appropriate moments to maintain natural conversation flow.
3Loss of information
If the system provides translation for every word spoken, then translation completeness is improved, but processing speed and real-time capability are worsened
Solution Approach 1:
The system applies partial translation by focusing on key segments of speech rather than processing every single word continuously. It identifies important phrases, sentences, or concepts for translation while allowing less critical utterances to pass through more quickly, balancing completeness with processing speed to maintain real-time capability.
Solution Approach 2:
The system uses periodic processing by analyzing speech in discrete time segments or phrases rather than continuously processing every word. It detects speech patterns, identifies when to activate translation, and processes translation in periodic intervals aligned with natural speech rhythms, maintaining both completeness and real-time performance.
Data Source
AI summary
Systems and methods for providing one-to-one and audio and video calls or for providing multi-party audio or video conferences also provide language translation services. When language translation services are provided, a party to a call or conference hears both the audio of the speaker, and a translated version of the speaker's audio.