Hearing Device Voice Loudness Feedback via Acoustic Thresholds
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Solution Overview
Problem
Users of hearing devices face difficulties in estimating their voice loudness, especially when using remote microphones or during streaming operations, leading to discomfort, and hearing-impaired children often raise their voice pitch due to nervousness or uncertainty about being understood.
Innovation Solution
A method that extracts the user's voice signal from audio signals acquired by the hearing device's microphone, determines the sound level, and provides feedback on whether the voice is too loud or too soft by setting minimal and maximal thresholds based on the acoustic situation, using a hearing device with a sound processor and potentially a portable device for notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a remote microphone or streaming device is used, then the microphone input of the hearing device is attenuated, but the user cannot accurately estimate their voice loudness
Solution Approach 1:
The system extracts the user's own voice signal from the audio signal, determines its sound level, and provides feedback to the user when the sound level falls outside a determined range. This closed-loop feedback mechanism enables accurate voice loudness estimation despite microphone attenuation in streaming modes.
Solution Approach 2:
The system introduces an intermediary processing layer that extracts the user's voice signal from the attenuated microphone input, analyzes its characteristics, and provides interpreted feedback. This intermediary process bridges the gap between attenuated input and accurate loudness estimation.
2Ease of operation
If the hearing device provides real-time voice loudness feedback, then user comfort is improved, but the device complexity increases
Solution Approach 1:
The hearing device autonomously extracts the user's voice signal, determines sound levels, identifies acoustic situations, and provides feedback without requiring manual user intervention. The system serves itself by automatically monitoring and adjusting parameters based on real-time analysis.
Solution Approach 2:
The system dynamically changes processing parameters based on the identified acoustic situation, selecting different minimal and maximal sound level thresholds appropriate for each environment. This adaptive parameter adjustment simplifies operation while maintaining sophisticated processing capabilities.
3Reliability
If hearing-impaired children are trained to maintain appropriate vocal levels, then communication effectiveness is improved, but the training process becomes more complex
Solution Approach 1:
The system provides continuous real-time feedback to children during training, immediately indicating when their voice is too loud or too soft. This immediate feedback loop accelerates the learning process and improves communication effectiveness without requiring complex manual training protocols.
Solution Approach 2:
The system replaces complex manual training methods with automated electronic feedback mechanisms. The hearing device itself becomes the training tool, substituting for manual instruction and simplifying the training process while maintaining reliability.
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
Enhances user comfort by providing real-time feedback on voice loudness, aiding in effective communication and training users, including children, to maintain appropriate vocal levels in various acoustic environments.
Implementation Method 1
a microphone for picking up voice data from a user
Data Source
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Figure 5
AI summary
A method for providing feedback of an own voice loudness of a user of a hearing device (12) comprises: extracting an own voice signal (42) of the user from an audio signal (30) acquired with a microphone (24) of the hearing device (12); determining a sound level (44) of the own voice signal (42) from the audio signal (30); determining an acoustic situation (48) of the user; determining at least one of a minimal threshold (46a) and a maximal threshold (46b) for the sound level (44) of the own voice signal (42) from the acoustic situation (48) of the user; and notifying the user, when the sound level (44) is at least one of lower than the minimal threshold (46a) and higher than the maximal threshold (46b).