Mode-Specific Echo Cancellation for Hearing Aid Audio Modes
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional echo cancellation techniques are inadequate for communication devices used by hearing-impaired users, as they struggle with louder volume levels, leading to ineffective echo removal during calls, especially when switching between different audio modes.
Innovation Solution
A communication device with a processor that loads specific sets of training parameters for an echo canceller based on the selected audio mode, updating and storing these parameters to adapt to changing echo characteristics, thereby improving echo cancellation performance across different modes such as handset, speakerphone, and headset.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional acoustic echo cancellation techniques are used, then the system can operate in different audio modes, but echo cancellation performance deteriorates due to louder volume levels and varying echo characteristics across modes
Solution Approach 1:
The echo canceller is divided into multiple mode-specific instances (handset mode echo canceller, speakerphone mode echo canceller, headset mode echo canceller), each trained on echo characteristics specific to that audio mode. This segmentation allows each instance to specialize in canceling echo for its designated mode, resolving the contradiction between reliable echo cancellation and adaptability to different modes.
Solution Approach 2:
The system dynamically selects and switches between different echo canceller instances based on the current audio mode. The processor determines which audio mode is active and activates the corresponding echo canceller, enabling the system to adapt its echo cancellation behavior to match the current operational context, thus maintaining reliable performance across varying conditions.
2Measurement precision
If a single set of training parameters is used for all audio modes, then device complexity is reduced, but echo cancellation precision deteriorates due to varying echo characteristics
Solution Approach 1:
The single set of training parameters is segmented into multiple mode-specific training parameter sets, each optimized for a specific audio mode. This allows the system to achieve high precision echo cancellation for each mode by using parameters trained on that mode's specific echo characteristics, rather than using a generic set that must compromise across all modes.
Solution Approach 2:
Training parameter sets for each audio mode are pre-computed and stored in memory during device initialization or manufacturing. When the device operates, the pre-trained parameters are directly loaded and applied without requiring real-time training, which maintains high precision while avoiding the computational complexity of adaptive training during operation.
3Adaptability or versatility
If the echo canceller continuously adapts parameters during operation, then adaptability to changing conditions improves, but loss of information increases due to parameter drift
Solution Approach 1:
The system implements dynamic switching between pre-trained mode-specific parameter sets based on detected audio mode changes, rather than continuous adaptation. This allows the system to adapt to changing conditions (different audio modes) while maintaining parameter integrity, as each mode has its own dedicated parameter set that doesn't suffer from drift caused by training on inappropriate data.
Solution Approach 2:
The processor continuously monitors the current audio mode and provides feedback to the echo canceller to select the appropriate parameter set. This feedback mechanism ensures that the correct pre-trained parameters are always in use, enabling adaptability to mode changes while preventing parameter drift by avoiding inappropriate continuous adaptation.
Data Source
AI summary
Methods and devices are disclosed for performing echo cancellation with a communication device for use by a hearing-impaired user. The communication device comprises communication elements, a memory device storing a plurality of sets of training parameters for an echo canceller, and a processor operably coupled with the communication elements and the memory device. The communication elements are configured to receive audio signals from a far end communication device, and to receive text captions corresponding to the audio signals from a relay service for display by the communication device during a call. Each set of training parameters corresponding to a different audio mode for the communication device. The processor is configured to execute an echo canceller by loading a first set of training parameters when a first audio mode is selected, and a second set of training parameters when a second audio mode is selected.