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Two-Microphone Hearing Aids Using Prediction Error Method for Adaptive Feedback Control
- Source :
- IEEE-ACM Transactions on Audio, Speech, and Language Processing; 2018, Vol. 26 Issue: 5 p909-923, 15p
- Publication Year :
- 2018
-
Abstract
- A challenge in hearing aids is adaptive feedback control which often uses an adaptive filter to estimate the feedback path. This estimate of the feedback path usually results in a bias due to the correlation between the loudspeaker signal and the incoming signal. The prediction error method (PEM) is a popular method for reducing this bias for adaptive feedback control (AFC) in hearing aids, providing a significant performance improvement compared to conventional adaptive feedback control techniques. However, the PEM-based AFC (PEM-AFC) applications are still limited to single-microphone single-loudspeaker (SMSL) systems. This paper investigates the application of the PEM-AFC to a two-microphone single-loudspeaker hearing aid with detailed theoretical analysis as well as practical experiments. In the proposed method, PEM-AFC2, we use the two-microphone adaptive feedback control (AFC2) method with two microphones and one loudspeaker. The incoming signals at the two microphones are related by a relative transfer function (RTF) which is used to predict the incoming signal at the main microphone. In addition, a prefilter is employed to prewhiten the loudspeaker and the microphone signals before the adaptive filter estimates. As a result, the proposed method obtains a lower bias and a faster tracking rate compared to the PEM-AFC and the AFC2 method, while still maintaining a good quality of the incoming signal. A new derivation for optimal filters in the AFC2 method will also be provided. The performance of the proposed method is evaluated for speech shaped noise as incoming signal and with undermodeling the RTF as well as with perfect modeling the RTF. Moreover, different types of incoming signals and a sudden change of feedback paths are also considered. The experimental results show that the proposed approach yields a significant performance improvement compared to existing state-of-the-art AFC methods such as the PEM-AFC and the AFC2.
Details
- Language :
- English
- ISSN :
- 23299290
- Volume :
- 26
- Issue :
- 5
- Database :
- Supplemental Index
- Journal :
- IEEE-ACM Transactions on Audio, Speech, and Language Processing
- Publication Type :
- Periodical
- Accession number :
- ejs45279242
- Full Text :
- https://doi.org/10.1109/TASLP.2018.2798822