Speech Audiometry Phoneme Scoring for Hearing Assessment
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Solution Overview
Problem
Existing audiometric testing methods lack efficient and accurate ways to assess a user's hearing ability and provide personalized treatment recommendations based on phonetic analysis of responses to target words.
Innovation Solution
A system and method that audibly provides target words, converts user responses to phonetic representations, and compares them with target word representations using algorithms like Levenshtein distance to determine phoneme scores, identifying error patterns and informing treatment actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated voice recognition is used to score audiometric responses, then scoring efficiency and consistency are improved, but accuracy in detecting subtle phonetic differences deteriorates
Solution Approach 1:
The patent introduces an intermediary layer between automated voice recognition and final scoring. A voice recognition system first transcribes user responses to text, then a separate phonetic analysis module converts the text to phonemes and compares them with target word phonemes. This intermediary phonetic analysis step ensures accurate detection of subtle phonetic differences while maintaining automated efficiency.
Solution Approach 2:
The patent replaces manual audiologist scoring with an automated computer-based system that uses voice recognition technology and algorithmic phonetic comparison. This substitution maintains high accuracy in phonetic differentiation while dramatically improving scoring efficiency and consistency across multiple users.
2Measurement precision
If detailed phonetic analysis is performed on user responses, then measurement precision of hearing abilities is improved, but device complexity increases
Solution Approach 1:
The patent employs a multi-functional text-to-phoneme conversion module that serves dual purposes: it converts user response text to phonemes for comparison with target words, and simultaneously identifies phonetic error patterns. This universal module provides detailed phonetic analysis for accurate hearing assessment without requiring separate complex analysis systems for each function.
Solution Approach 2:
The system pre-stores phoneme representations of all target words in the audiometric test database. When a user responds, the system only needs to convert the user's text response to phonemes and compare against the pre-prepared target phonemes, rather than performing complete phonetic analysis from scratch. This preliminary preparation reduces real-time computational complexity while maintaining detailed analysis capability.
3Measurement precision
If phoneme-by-phoneme comparison is used to analyze responses, then measurement precision is improved, but processing time increases
Solution Approach 1:
The patent replaces time-consuming manual phoneme-by-phoneme comparison with automated algorithmic processing. The computer system automatically converts user response text to phonemes using text-to-phoneme conversion algorithms, then systematically compares each phoneme with target word phonemes using efficient string matching algorithms, dramatically reducing processing time while maintaining precise error detection.
Solution Approach 2:
The system performs self-scoring by automatically comparing user responses with correct answers and generating phoneme scores without requiring audiologist intervention for each comparison. The automated phonetic analysis and error pattern identification enable the system to process multiple responses rapidly, reducing overall processing time while maintaining high measurement precision.
Data Source
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AI summary
This application relates to audiometric testing techniques. An example implementation is based on audibly providing a target word to a user and receiving a response of what the user audibly perceived in text form. The text is then converted into phonemes and compared with phonemes of the target word. In many examples, the process is repeated for multiple target words. The resulting comparison data can be used to determine the user's ability to hear and can be the basis for one or more treatment actions if the results reveal the user may suffer from hearing loss. The treatment actions can include providing the user with a hearing device or modifying an existing hearing device of the user.