Semantic Unit Set Improvement via Phonetic Sound Feedback
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Solution Overview
Problem
Existing voice recognition and text input systems face challenges in deriving high-quality semantic unit sets due to variations in locution habits, indistinct pronunciations, regional dialects, and environmental noise, leading to inaccuracies in voice recognition and text input.
Innovation Solution
A method that improves semantic unit sets using an enhancement phonetic sound, where a user-provided phonetic sound is used to specify and replace matched semantic units within a captured set, enhancing the quality of voice recognition and text input results, regardless of the input method (voice or text) through a device with voice sensing, processing, and semantic unit improving units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If voice recognition techniques are used to obtain semantic unit sets, then the system can process human voice input, but the quality and accuracy of the semantic unit sets deteriorate due to locution habits, indistinct pronunciations, regional dialects, and environmental noise
Solution Approach 1:
The patent implements a feedback mechanism where the system compares the initially recognized semantic unit set with a reference semantic unit set, identifies mismatches, and allows users to provide corrective phonetic inputs. This feedback loop continuously improves recognition accuracy by learning from user corrections and adjusting the semantic unit set accordingly.
Solution Approach 2:
The patent introduces an intermediary improvement phonetic sound that mediates between the noisy voice input and the target semantic unit set. This intermediary element serves as a bridge to refine the recognition results by comparing intermediate semantic unit sets with reference sets and applying corrective transformations.
2Adaptability or versatility
If standard voice recognition processing is applied, then the system can handle various pronunciations and dialects, but the accuracy of the resulting semantic unit sets decreases
Solution Approach 1:
The patent performs preliminary actions by pre-storing reference semantic unit sets and preparing improvement phonetic sounds before the actual recognition process. This preliminary preparation enables the system to quickly compare and correct recognition results, improving reliability without sacrificing adaptability to various pronunciations.
Solution Approach 2:
The patent changes parameters by transforming the initial semantic unit set into an improved version through phonetic sound comparison and substitution. By adjusting the semantic units based on phonetic similarity and reference comparisons, the system maintains adaptability while improving recognition accuracy.
3Measurement precision
If manual correction of voice recognition results is implemented, then the accuracy of semantic unit sets improves, but the time and complexity of the processing increases
Solution Approach 1:
The patent implements self-service by enabling the system to automatically compare recognition results with reference semantic unit sets and identify corrections needed. This automated self-correction process reduces manual intervention time while maintaining high accuracy, as the system independently performs the correction workflow.
Solution Approach 2:
The patent applies partial action by focusing correction efforts only on the specific semantic units that show mismatches with the reference set, rather than manually reviewing the entire semantic unit set. This selective correction approach significantly reduces processing time while maintaining high accuracy.
Data Source
AI summary
The present invention relates to a method, an apparatus, and a computer-readable recording medium for improving at least one semantic unit set by using a phonetic sound. The method for improving a set including at least one semantic unit, in which the set including at least one semantic unit is a captured semantic unit set, includes: receiving an improvement phonetic sound according to utterance of a user; specifying an improvement semantic unit set on the basis of the improvement phonetic sound; specifying a semantic unit set as a target to be actually improved within the captured semantic unit set, as a matched semantic unit set, on the basis of correlation thereof with the improvement semantic unit set; and replacing the matched semantic unit set within the captured semantic unit set with the improvement semantic unit set.