Fluency Shaping Error Detection via Voice Energy Analysis
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Solution Overview
Problem
Conventional speech therapy techniques for fluency shaping, such as those used for stuttering, are ineffective for remote practice and lack real-time feedback, making it difficult for patients to maintain fluency outside the clinical setting.
Innovation Solution
A system and method for detecting errors in fluency shaping exercises using a network-based system that analyzes voice production energy levels, provides real-time feedback, and generates visual cues to guide patients in improving their speech motor skills, allowing for remote therapy and personalized practice sessions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional speech therapy techniques are used in clinical settings, then speech fluency can be improved through therapist guidance, but the therapy cannot be effectively practiced remotely without real-time feedback
Solution Approach 1:
The system captures voice production during fluency shaping exercises, analyzes energy levels to detect speech errors, and provides immediate visual feedback through a user interface. This closed-loop feedback mechanism enables remote practice by replacing the therapist's real-time guidance with an automated system that continuously monitors and evaluates speech patterns, allowing patients to practice independently while receiving objective performance information.
Solution Approach 2:
The system introduces an intermediary computational layer between the patient's speech production and the therapy evaluation process. This intermediary analyzes voice energy levels, compares them against target patterns, and translates complex speech motor skill assessments into simple visual feedback, enabling remote therapy without requiring direct therapist involvement during practice sessions.
2Reliability
If speech motor skills are trained in the clinic with therapist modeling, then fluency can be improved, but patients cannot maintain fluency outside the clinic due to lack of continuous practice guidance
Solution Approach 1:
The system enables patients to independently monitor and evaluate their own speech performance during remote practice sessions. By providing automated error detection and visual feedback, the system allows patients to self-correct speech patterns without requiring therapist presence, fostering autonomous practice and consistent fluency maintenance in everyday environments.
Solution Approach 2:
The system monitors changes in voice production parameters, specifically energy levels across different frequency ranges, to detect deviations from target speech patterns. By tracking these physical parameters objectively, the system provides reliable feedback on fluency maintenance without requiring complex clinical assessment tools, simplifying the therapy system while improving reliability.
3Measurement precision
If EMG devices are used to monitor muscle activity, then speech motor skill performance can be measured, but the devices cannot provide real-time guidance to improve performance
Solution Approach 1:
The system provides real-time visual feedback by displaying detected speech errors and comparing them against target patterns during the exercise. This immediate feedback loop allows patients to understand their performance and make corrections during practice, transforming precise measurement capability into actionable guidance without requiring complex EMG equipment.
Solution Approach 2:
The system replaces complex mechanical EMG measurement systems with acoustic analysis of voice production. By analyzing energy levels in voice signals, the system achieves sufficient measurement precision for detecting speech errors while providing real-time guidance through software-based feedback, eliminating the need for cumbersome physical sensors and complex hardware setups.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables effective remote speech therapy by providing immediate and objective feedback, improving speech fluency and reducing frustration and anxiety, as patients can practice and receive guidance on speech motor skills development outside clinical settings.
Implementation Method 1
analyzing a voice production to compute a set of first energy levels composing the voice production
Data Source
AI summary
A method and system for detecting errors when practicing fluency shaping exercises. The method includes setting each threshold of a set of thresholds to a respective predetermined initial value; analyzing a voice production to compute a set of first energy levels composing the voice production, wherein the voice production is of a user practicing a fluency shaping exercise; detecting at least one speech-related error based on the computed set of first energy levels, a set of second energy levels, and the set of thresholds, wherein the detection of the at least one speech-related error is with respect to the fluency shaping exercise being practiced by the user, wherein the set of second energy levels is determined based on a calibration process; and generating feedback indicating the detected at least one speech-related error.