Speech Recognition Correction Using Dual Language Processing
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Solution Overview
Problem
Current speech recognition systems often produce erroneous translations, requiring users to reiterate corrections which may not accurately correct the wrongly-translated words due to high probabilities of re-translation errors.
Innovation Solution
A method and apparatus that utilize a second language to correct wrongly-translated words by switching speech recognition between the first and second languages when a word is selected for correction, using Natural Language Processing engines and logic circuitry to determine the most likely correction based on both languages' inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If speech recognition is performed using a single language, then the system is simple to operate, but the translation accuracy deteriorates when erroneous words need correction
Solution Approach 1:
The speech recognition system is designed to handle multiple languages (first language and second language) within a single system framework. The logic circuitry automatically detects which language is being spoken and routes the speech to the appropriate language-processing engine, enabling the system to function universally across different languages without requiring separate systems for each language.
Solution Approach 2:
The system dynamically switches between different language-processing engines based on real-time language detection. When a user selects a wrongly-translated word and re-speaks it, the system determines whether the correction is in the first or second language and activates the corresponding processing engine, making the system adaptable and dynamic rather than static.
2Reliability
If a user reiterates a wrongly-translated word in the same language, then the correction process is simple, but the probability of re-translation error increases
Solution Approach 1:
The system introduces a second language as an intermediary medium for correction. When a user encounters a wrongly-translated word, they can select it and re-speak the correct word in the second language. The logic circuitry detects the second language, processes it through the appropriate engine, and translates it back to the first language, using the second language as a mediator to bypass the original translation error.
Solution Approach 2:
Instead of requiring the user to re-speak the correction in the same language (which leads to repeated errors), the system inverts the approach by accepting corrections in a different language (second language). This inversion allows the system to leverage the user's ability to express the correct concept in another language, thereby improving correction reliability.
3Measurement precision
If the system uses multiple languages for correction, then the translation accuracy improves, but the device complexity increases
Solution Approach 1:
The speech recognition system is segmented into distinct language-processing engines, each specialized for a specific language. The logic circuitry includes a language detection component that segments the input processing based on detected language, routing first language speech to the first language-processing engine and second language speech to the second language-processing engine. This segmentation allows each engine to be optimized for its specific language while maintaining overall system accuracy.
Solution Approach 2:
The system changes the language parameter dynamically based on detection. When the language detection component identifies second language speech during correction mode, it changes the processing parameter to activate the second language-processing engine. This parameter change allows the system to adapt its processing capabilities to match the input language, improving accuracy without requiring all engines to run simultaneously.
Data Source
AI summary
A method and apparatus for correcting a wrongly-translated word in a device employing speech recognition is provided herein. During operation, a device will use a second language to correct a wrongly-translated word that was wrongly translated using a first language. More particularly, after speech recognition is performed using the first language, when a user selects text to be corrected, the user will utter the speech again using the second language that differs from the first language. Both the first and the second language can be used by the device to determine a best translation of the speech.