Cross-Language Voice Feature Correction for Cognitive Function Estimation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for estimating oral and cognitive functions based on a specific language face accuracy issues when applied to languages with different voice features, leading to decreased estimation accuracy.
Innovation Solution
An estimation method that corrects voice features of a subject speaking a first language to align with those of a second language by analyzing voice features of individuals speaking both languages and applying correction expressions or trained models to match distributions, enabling accurate estimation of oral and cognitive functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If an estimation process based on a specific language is applied to a language different from the specific language, then the estimation can be performed, but the accuracy of estimation decreases
Solution Approach 1:
The patent applies parameter changes by adjusting voice feature parameters to transform the voice feature group of the first language into a corrected voice feature group that matches the distribution characteristics of the second language. This involves calculating correction expressions based on the relationships between voice feature groups of different languages and applying these corrections to maintain estimation accuracy when evaluating speakers of languages different from the training language.
2Adaptability or versatility
If voice features of speakers of a first language are analyzed to estimate oral or cognitive function, then the estimation can be performed, but the voice features differ from those of the second language reducing estimation accuracy
Solution Approach 1:
The patent uses an intermediary approach by introducing a corrected voice feature group as a mediator between the original voice feature group of the first language and the target voice feature group of the second language. The correction process acts as a transformation intermediary that adjusts the voice features to bridge the distributional differences between languages, enabling accurate estimation without requiring direct matching of original voice features.
Data Source
AI summary
An estimation method includes: obtaining a first voice feature group of a plurality of persons who speak a first language; obtaining a second voice feature group of a plurality of persons who speak a second language; obtaining a voice feature of a subject; correcting the voice feature of the subject according to a relationship between the first voice feature group and the second voice feature group; estimating, from the voice feature of the subject that has been corrected, an oral function or a cognitive function of the subject by using an estimation process for an oral function or a cognitive function based on the second language; and outputting a result of estimation of the oral function or the cognitive function of the subject.