Abstract
A recent trend in hearing aids is the connection of the left and right devices to collaborate between them. Binaural systems can provide natural binaural hearing and support the improvement of speech intelligibility in noise, but they require data transmission between both devices, which increases the power consumption. This paper presents a novel sound source separation algorithm for binaural speech enhancement based on supervised machine learning and time-frequency masking. The system is designed considering the power restrictions in hearing aids, constraining both the computational cost of the algorithm and the transmission bit rate. The transmission schema is optimized using a tailored evolutionary algorithm that assigns a different number of bits to each frequency band. The proposed algorithm requires less than 10% of the available computational resources for signal processing and obtains good separation performance using bit rates lower than 64 kbps.
Highlights
Most people suffering from impaired hearing and wearing hearings aids show a lack of intelligibility when they are in a noisy environment
The implementation of signal processing algorithms in hearing aids presents additional challenges: the reduced battery life, which limits the computational capability of the device, the requirement of real-time processing, which limits the processing delay to few milliseconds and reduces the number of frequency bands used for the analysis, and the small size of the device, which limits the number of assembled microphones
Our previous work in [31] addressed the same problem described in this paper, designing a low-cost speech separation system based on the computation of the timefrequency binary mask that maximizes the W-disjoint orthogonality (WDO) factor and increases the energy efficiency of the wireless-communicated binaural hearing aids
Summary
Most people suffering from impaired hearing and wearing hearings aids show a lack of intelligibility when they are in a noisy environment. The communication between both hearing devices should be implemented with a wireless link, due to aesthetic reasons, which unavoidably increases the power consumption and, reduces the battery life This fact opens a new problem: how to reduce the bit rate transmitted between both devices without decreasing the performance of the speech enhancement algorithm. Our previous work in [31] addressed the same problem described in this paper, designing a low-cost speech separation system based on the computation of the timefrequency binary mask that maximizes the W-disjoint orthogonality (WDO) factor and increases the energy efficiency of the wireless-communicated binaural hearing aids. Where the time-frequency bins are associated to the source that has more energy than its interfering sources It has been demonstrated in [18,19,20] that the application of the IBM to separate speech from noise entails an improvement in the intelligibility of the target speech signal. The WDO factor is a good indicator of the quality of the separation achieved by a time-frequency mask for approximately WDO sources
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