Speech-Based Language Area Invasion Screening for Brain Disease
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Solution Overview
Problem
Conventional methods for determining brain language area invasion in patients with brain diseases involve subjective medical expert interpretations and expensive procedures like MRI, necessitating a more objective and cost-effective screening method.
Innovation Solution
A machine learning-based approach using speech data, including neural networks and ensemble techniques, to determine brain language area invasion through training and testing utterance data, incorporating brain image-based data and utterance function evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods using MRI and expert interpretation are used to determine brain language area invasion, then measurement precision is improved, but cost and device complexity increase significantly
Solution Approach 1:
The patent replaces complex medical imaging equipment (MRI machines) and manual expert interpretation processes with an automated speech processing system using machine learning models. The speech-based determination system substitutes the mechanical and procedural complexity of MRI scanning, image analysis, and expert consultation with computational algorithms that process speech data to determine language area invasion.
2Measurement precision
If MRI and expert interpretation methods are used, then measurement precision is improved, but loss of time increases due to expensive and complex procedures
Solution Approach 1:
The patent performs preliminary speech data collection and processing that can be done quickly without requiring time-consuming MRI scanning procedures. By using speech data as the primary input, the system eliminates the need for lengthy imaging procedures and expert review processes, achieving rapid determination while maintaining accuracy through pre-trained machine learning models.
3Device complexity
If speech data-based machine learning method is used, then device complexity and cost are reduced, but measurement precision may deteriorate compared to MRI methods
Solution Approach 1:
The patent transforms the determination approach by changing the input parameters from complex imaging data (MRI scans, tractography results) to simpler speech data parameters. By using speech features such as phonation characteristics, articulation patterns, and language processing metrics, the system achieves accurate determination through alternative measurable parameters that are easier and cheaper to obtain while maintaining diagnostic precision.
Data Source
AI summary
Disclosed is a language area invasion determination apparatus including a memory unit including a language area invasion determination model, and a processor that controls an operation of the language area invasion determination model included in the memory unit. The processor trains the language area invasion determination model by using one or more training utterance data and outputs language area invasion determination data of an examiner by using test utterance data and the trained language area invasion determination model. The training utterance data and the test utterance data include utterance speech data of a speaker.