Speech Translation Selective Processing for Reduced Delay
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Solution Overview
Problem
Existing automatic speech translation technologies suffer from delays and inefficiencies in processing time due to unnecessary operations in speech recognition, translation, and synthesis stages, particularly when users understand parts of the conversation.
Innovation Solution
An electronic device employs an AI system, specifically an artificial neural network, to determine a translation level based on user information such as language proficiency, age, gender, and environment, and selectively omits or summarizes translations to minimize delay by recognizing and translating only necessary parts of the speech signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complete speech recognition, translation, and synthesis stages are performed, then translation accuracy is improved, but delay time increases
Solution Approach 1:
The patent extracts and processes only the necessary parts of the speech signal for translation. The speech processing unit identifies and processes only those portions of the speech signal that require translation, rather than processing the entire speech signal through all stages. This selective extraction reduces processing time while maintaining translation accuracy for the relevant content.
Solution Approach 2:
The patent applies partial action by performing complete translation processing only on necessary portions of the speech signal. The speech processing unit determines which parts of the speech signal require translation and applies full processing (recognition, translation, synthesis) only to those parts, while other parts receive minimal or no processing. This reduces overall processing time while maintaining accuracy where needed.
2Loss of information
If translation is performed for all speech content, then completeness of translation is improved, but processing efficiency deteriorates
Solution Approach 1:
The speech processing unit extracts only the necessary portions of the speech signal that require translation. By identifying and separating the necessary parts from unnecessary parts, the system processes only relevant content through the complete translation pipeline, ensuring completeness for necessary content while improving processing efficiency by excluding redundant content.
Solution Approach 2:
The system applies partial processing action by performing complete translation (speech recognition, machine translation, speech synthesis) only on necessary portions of the speech signal. Other portions receive minimal processing or are skipped entirely. This ensures that all necessary information is translated completely while significantly improving processing efficiency by avoiding redundant operations on unnecessary content.
3Loss of time
If speech signal processing is minimized, then delay time is reduced, but translation accuracy for necessary parts deteriorates
Solution Approach 1:
The patent applies local quality by providing different levels of processing quality to different parts of the speech signal. Necessary parts receive complete and accurate processing (full speech recognition, translation, and synthesis), while unnecessary parts receive minimal or no processing. This ensures high translation accuracy for necessary content while reducing overall processing time through selective minimal processing of other content.
4Adaptability or versatility
If user-specific translation levels are applied, then translation quality matching user needs is improved, but system complexity increases
Solution Approach 1:
The patent implements dynamics by making the translation processing level adaptive and changeable based on user characteristics and context. The speech processing unit dynamically adjusts the level of processing applied to different speech signals based on stored user information (language proficiency, age, gender) and situational context. This allows the system to match translation quality to user needs while managing complexity through automated adaptive logic rather than fixed complex configurations.
Data Source
AI summary
A method and an electronic device for translating a speech signal between a first language and a second language with minimized translation delay by translating fewer than all words of the speech signal according to a level of understanding of the second language by a user that receives the translation.