In this letter we derive an optimal time-varying smoothing factor for smoothing non-stationary power spectra of a target signal when a noisy observation of this signal is given. The proposed approach is based on a complex Gaussian signal model in the short-time discrete Fourier domain and on mean squared error optimization. We find that the optimal smoothing factor depends on the signal-to-noise ratio as well as on the deviation between the smoothed estimate and the target signal power spectra. We investigate the properties of the proposed adaptive smoothing system and demonstrate its utility in a basic validation experiment.

The use of a nearby external microphone for addressing front-back ambiguity in single-microphone hearing aid devices is investigated. Strategic placement of the external microphone is able to provide benefits from the body shielding back-directional noise and therefore information for discriminating between the frontal and back hemispheres. The scattering effects of the body are first analyzed to yield a placement strategy of the external microphone for maximizing the shielding effect of the body against back-directional noise sources while also optimizing for speech intelligibility. Assuming optimal placement, a frontal target source presence probability (FTSPP) estimator is derived. Using the FTSPP estimator, a more comprehensive noise estimator is proposed, which considers both stationary and nonstationary interferers. The performance of the proposed noise estimator is evaluated in its application for postfiltering the output of a binaural beamformer. The effect of postfiltering using the proposed noise estimator is to provide further reduction of directional noise from the lateral and back direction while preserving the frontal target signal. The resulting enhancement with the proposed noise estimator provides a better signal-to-noise ratio and improved objective speech quality and intelligibility of a frontal target speaker compared to the state of the art.

We propose an approach to compute the inter-subband correlation (ISBC) of noisy speech signals to distinguish between speech and noise segments in the time-frequency plane. The proposed spectral correlation estimator provides information about the input signal which can be used to derive a binary mask or the speech-presence probability. Unlike other approaches it does not require an estimate of the noise power. To this end we analyse a received noisy speech signal in the modulation domain and identify similarly modulated subband signals within a range of modulation frequencies that are typical for speech signals. Based on this pre-processing step, we identify a single reference subband that most likely contains speech and estimate the spectral correlations with respect to this reference band. The algorithm proposed in this paper aims at a very low computational complexity which makes it suitable for hearing aids.

This paper presents a strategy for using an external microphone for enhancing noisy speech in single-microphone completely-in-canal (CIC) hearing aids. The external microphone is placed such that it benefits from the body shielding noise from the back hemisphere. The presented algorithm first enhances the external microphone signal without assuming an exact known location of the external microphone. The proposed algorithm then automatically incorporates the enhanced external microphone signal for post-processing enhancement of a conventional dual-channel binaural beamformer whenever the external microphone has a significant SNR advantage. The overall enhancement scheme avoids error-prone estimations of target voice activity detection and relative transfer functions between the microphones. Unlike single-channel post-processing filters which are limited to reducing stationary or diffuse noise, the proposed postprocessing filter is able to reduce highly non-stationary directional noise from the back hemisphere. The resulting system provides enhancement even for noise arriving from the backward direction, which conventionally is difficult for CIC hearing aids where there exists a front-back ambiguity.

Acoustic feedback is a well-known phenomenon in hearing aids. Under certain conditions, it causes the so-called howling effect, which is highly annoying for the hearing aid user and limits the maximum amplification of the hearing aid. The standard adaptive feedback cancellation algorithms suffer from a biased adaptation if the input signal is spectrally colored or tonal, as it is for speech and music signals. Due to this bias distortion artifacts (entrainment) are generated. In this letter, we present a method to detect tonal, high correlated parts of the input signal. In particular, the method is able to distinguish between correlation resulting from the input signal and from feedback path changes. A subband feedback cancellation system which applies decorrelation methods is the basis for the proposed method. Additionally, we suggest to use the correlation detection to increase the performance of the mentioned feedback cancellation system. The performance is measured by preventing entrainment and reacting to feedback path changes.

The filter-bank system implemented in hearing aids has to fulfill various constraints such as low latency and high stop-band attenuation, usually at the cost of low frequency resolution. In the context of frequency-domain noise-reduction algorithms, insufficient frequency resolution may lead to annoying residual noise artifacts since the spectral harmonics of the speech cannot properly be resolved. Especially in case of female speech signals, the noise between the spectral harmonics causes a distinct roughness of the processed signals. Therefore, this work proposes a two-stage filter-bank system, such that the frequency resolution can be improved for the purpose of noise reduction, while the original first-stage hearing-aid filter-bank system can still be used for compression and amplification. We also propose methods to implement the second filter-bank stage with little additional algorithmic delay. Furthermore, the computational complexity is an important design criterion. This finally leads to an application of the second filter-bank stage to lower frequency bands only, resulting in the ability to resolve the harmonics of speech. The paper presents a systematic description of the second filter-bank stage, discusses its influence on the processed signals in detail and further presents the results of a listening test which indicates the improved performance compared to the original single-stage filter-bank system.

Acoustic feedback is a well-known phenomenon in hearing aids. Under certain conditions it causes the so-called howling effect, which is highly annoying for the hearing aid user and limits the maximum amplification of the hearing aid. The standard adaptive feedback cancellation algorithms suffer from a biased adaptation if the input signal is spectrally colored, as it is for speech and music signals. Due to this bias distortion artifacts (entrainment) are generated. In this paper, we present a sub-band feedback cancellation system which combines decorrelation methods with a new realization of a known non-parametric variable step size. To apply this step size in the context of adaptive feedback cancellation, a method to estimate the signal power of the desired input signal, i.e., without feedback, is necessary. A major part of this paper is spent with the theoretical derivation of this estimate. Furthermore, the complete system is evaluated extensively for several speech and music signals as well as for different feedback scenarios in simulations with feedback paths measured in concrete applications as well as for real-time simulations with hearing aid dummies. Both use hearing loss compensation methods as applied in physical hearing aids. The performance is measured in terms of being able to prevent entrainment and to react to feedback path changes. For both simulation setups the system shows a good performance with respect to the two performance measures. Furthermore, the overall feedback cancellation method relies only on few parameters, shows a low computational complexity, and therefore has a strong practical relevance.

Standard adaptive feedback cancellation algorithms in hearing aids suffer from a biased adaptation if the input signal is spectrally colored, as it is for tonal signals, like music. Due to that, distortion artifacts (entrainment) are generated. In this paper, a sub-band feedback cancellation system is presented combined with an adaptation control to deal with those signals. Two control concepts for determining the variable step sizes [1, 2], known from general adaptive filter algorithms, are theoretically and practically analyzed and evaluated for an application to feedback cancellation. For feedback cancellation the control is combined with known methods to reduce the bias, such as prediction error filtering or frequency shifting. Based on this combination, a completely new setup for feedback cancellation is proposed. It relies entirely on signals accessible in real systems, shows a low computational complexity, and therefore has a strong practical relevance.

We present a new codebook-based speech enhancement approach which is able to increase robustness of conventional codebook-based approaches against model mismatch and unknown noise types. This is achieved by training only the difference between the actual noise and a robust estimate (e.g., obtained by minimum statistics or recursive minimum tracking) in the cepstral domain instead of the noise itself. The noise codebook is then generated by shifting the so obtained delta-codebook by the cepstral representation of a robust noise estimate. We use the recursive minimum tracking approach as robust estimate. It is thus guaranteed that the robust estimate is also a valid estimate of the codebook-based algorithm. Consequently, the codebook-based algorithm inherits the robustness from the recursive minimum tracking approach. Objective and subjective experiments show that the proposed method yields a consistent quality improvement over the basic codebook-based approach and recursive minimum tracking.

An implementation of a complete hands-free telephone system on a low-cost DSP with 16-bit fixed-point arithmetic is presented. The prototype, consisting of an adaptive echo canceller, was developed for an industrial customer. The main emphasis is laid on the control unit of the system being necessary for a reliable performance in all environments and the attenuation introduced by the loss control unit. Keeping the loss as small as possible, which is most important for a natural communication including full double-talk capabilities, requires exact knowledge of the current system performance and the background noise level. In case of background noise the applied total loss is adjusted to the power of the noise. The measures we used and their application to our system control are discussed.