Temporal Speech Scoring for Behavioral Analysis
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Solution Overview
Problem
Current technologies fail to effectively quantify behavioral aspects of speakers in verbal interactions based on temporal attributes, and determine the need for intervention in interactions such as service calls, due to limitations in analyzing non-verbal expressions and mood detection.
Innovation Solution
A voice acquisition apparatus coupled with processors analyzes temporal variations in speech, correlating them with reference patterns to derive quantitative scores indicating behavioral aspects and determining the necessity and nature of intervention in verbal interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If temporal characteristics of speech are analyzed to quantify behavioral aspects, then measurement precision of behavioral metrics is improved, but device complexity increases due to need for sophisticated analysis systems
Solution Approach 1:
The system segments the complex task of behavioral analysis into distinct temporal characteristics (pause duration, speech rate, turn-taking patterns) that can be analyzed separately and then integrated to produce comprehensive behavioral scores
Solution Approach 2:
The patent introduces intermediate processing layers including feature extraction modules and reference pattern databases that mediate between raw speech signals and final behavioral scores, simplifying the overall system architecture
2Reliability
If real-time analysis of temporal speech characteristics is performed, then responsiveness to interaction dynamics is improved, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-processing speech signals to extract temporal features in real-time and maintaining reference pattern databases in advance, enabling rapid comparison and scoring without extensive processing delays
Solution Approach 2:
The patent applies partial action by focusing analysis on specific critical temporal characteristics rather than analyzing all speech features, and uses selective scoring approaches that process only the most relevant interaction dynamics
3Loss of information
If quantitative scores of behavioral aspects are derived from temporal characteristics, then information completeness about speaker state is improved, but difficulty of detecting and measuring increases
Solution Approach 1:
The system transforms complex speaker state information into standardized quantitative score parameters that represent different behavioral aspects (emotional state, engagement level, turn-taking behavior), making the information more measurable and comparable
Solution Approach 2:
The patent replaces manual analysis of temporal characteristics with automated computational algorithms that detect and measure speech patterns, eliminating the need for human analysts to manually assess temporal features
Data Source
AI summary
A method and apparatus for speech analysis, comprising detecting an at least one temporal characteristic of an at least one speech of an at least one speaker, and deducing an at least one quantitative score from the at least one temporal characteristic, where the at least one quantitative score indicates an at least one extent of an at least one behavioral aspect of the at least one speaker.