Speech Analysis Device Dynamic Dictionary Segmentation
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Solution Overview
Problem
Existing automated personality analysis methods based on word choice are limited in determining arbitrary characteristics of a person and rely on static keyword lists, which result in incomplete and context-dependent evaluations.
Innovation Solution
A method and device that utilize a comprehensive dictionary file covering at least 80% of language file words, categorizing them into various parts of speech and semantic environments, allowing for statistical and algorithmic analysis to derive characteristics from voice files, enabling the analysis of broader language patterns and psychological states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If static keyword lists are used for automated personality analysis, then the analysis process is simple and fast, but the analysis coverage is limited and incomplete
Solution Approach 1:
The patent transforms the static keyword list into a dynamic dictionary file that is automatically updated and expanded during operation. The system starts with an initial dictionary but continuously incorporates new words encountered in analyzed language files, making the dictionary adaptive and growing over time to improve coverage without sacrificing analysis speed.
Solution Approach 2:
The patent performs preliminary organization of language files into categories (e.g., by topic, source, or characteristics) before analysis. This pre-categorization allows the system to efficiently select and apply appropriate dictionary files or analysis parameters, maintaining fast processing while ensuring comprehensive coverage through targeted dictionary selection.
2Reliability
If a comprehensive dictionary file covering 80%+ of words is used, then analysis coverage and reliability improve, but processing complexity and computational resources increase
Solution Approach 1:
The patent divides the comprehensive dictionary file into multiple smaller, specialized dictionary files organized by categories (e.g., personality traits, emotions, topics). Instead of loading one massive dictionary, the system selectively loads and applies only the relevant category-specific dictionaries needed for each analysis task, reducing memory requirements and processing complexity while maintaining comprehensive coverage.
Solution Approach 2:
Different portions of the language file are analyzed using different specialized dictionary files tailored to specific characteristics or topics. The system applies local quality by matching the appropriate dictionary to the specific segment being analyzed, ensuring high reliability for each category without the overhead of processing the entire comprehensive dictionary for every word.
3Device complexity
If only predetermined keyword lists are analyzed, then the analysis method remains simple, but it cannot determine arbitrary characteristics of a person
Solution Approach 1:
The patent creates a universal dictionary file structure that can analyze multiple types of characteristics through a single integrated system. The dictionary files are designed with standardized categories and metadata that enable the same analysis framework to determine personality traits, emotional states, cognitive characteristics, and other arbitrary characteristics by simply changing the active dictionary file or category filters, not the underlying method.
Solution Approach 2:
The system maintains simplicity by keeping the core analysis method unchanged while achieving versatility through parameter changes—specifically, by switching between different dictionary file configurations, category selections, and weighting parameters. This allows the same simple algorithm to adapt to analyzing different characteristics by adjusting which dictionary file is active and how results are aggregated.
4Loss of time
If intermediate results are output during speech file acquisition, then real-time feedback capability improves, but processing time and system response requirements increase
Solution Approach 1:
The patent implements periodic output of intermediate results at predetermined intervals (e.g., after analyzing a certain number of words or time segments) rather than continuously processing and outputting every word. This periodic action provides timely feedback to reduce perceived delay while maintaining high processing throughput by batching operations and avoiding constant interrupt handling.
Data Source
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AI summary
The invention relates to a method for wording-based speech analysis. In order to provide a method that allows automated analysis of largely arbitrary features of a person from whom a voice file that needs to be analysed comes, the invention detaches itself from the known concept of evaluating static keyword lists for the personality type. The method according to the invention comprises the preparation of a computer system by formation of a reference sample that allows the comparison that is necessary for feature recognition with other persons. The preparation of the computer system involves the recording and storage of a further voice file in addition to the voice files of the reference sample, the analysis of the additionally recorded voice file and the output of the recognized features using at least one output unit connected to the computer system. Furthermore, the invention relates to a speech analysis device for carrying out the method.