Digital signal processing algorithms for noise reduction, dynamic range compression, and feedback cancellation in hearing aids

Hearing loss can be caused by many factors, e.g., daily exposure to excessive noise in the work environment and listening to loud music. Another important reason can be age-related, i.e., the slow loss of hearing that occurs as people get older. In general hearing impaired people suffer from a frequency-dependent hearing loss and from a reduced dynamic range between the hearing threshold and the uncomfortable level. This means that the uncomfortable level for normal hearing and hearing impaired people suffering from so called sensorineural hearing loss remains the same but the hearing threshold and the sensitivity to soft sounds are shifted as a result of the hearing loss. To compensate for this kind of hearing loss the hearing aid should include a frequency-dependent and a level-dependent gain. The corresponding digital signal processing (DSP) algorithm is referred to as dynamic range ...

Ngo, Kim — KU Leuven


Design and evaluation of noise reduction techniques for binaural hearing aids

One of the main complaints of hearing aid users is their degraded speech understanding in noisy environments. Modern hearing aids therefore include noise reduction techniques. These techniques are typically designed for a monaural application, i.e. in a single device. However, the majority of hearing aid users currently have hearing aids at both ears in a so-called bilateral fitting, as it is widely accepted that this leads to a better speech understanding and user satisfaction. Unfortunately, the independent signal processing (in particular the noise reduction) in a bilateral fitting can destroy the so-called binaural cues, namely the interaural time and level differences (ITDs and ILDs) which are used to localize sound sources in the horizontal plane. A recent technological advance are so-called binaural hearing aids, where a wireless link allows for the exchange of data (or even microphone signals) between the ...

Cornelis, Bram — KU Leuven


Analysis, Design, and Evaluation of Acoustic Feedback Cancellation Systems for Hearing Aids

Acoustic feedback problems occur when the output loudspeaker signal of an audio system is partly returned to the input microphone via an acoustic coupling through the air. This problem often causes significant performance degradations in applications such as public address systems and hearing aids. In the worst case, the audio system becomes unstable and howling occurs. In this work, first we analyze a general multiple microphone audio processing system, where a cancellation system using adaptive filters is used to cancel the effect of acoustic feedback. We introduce and derive an accurate approximation of a frequency domain measure—the power transfer function—and show how it can be used to predict system behaviors of the entire cancellation system across time and frequency without knowing the true acoustic feed-back paths. Furthermore, we consider the biased estimation problem, which is one of the most challenging ...

Guo, Meng — Aalborg University


Multi-microphone noise reduction and dereverberation techniques for speech applications

In typical speech communication applications, such as hands-free mobile telephony, voice-controlled systems and hearing aids, the recorded microphone signals are corrupted by background noise, room reverberation and far-end echo signals. This signal degradation can lead to total unintelligibility of the speech signal and decreases the performance of automatic speech recognition systems. In this thesis several multi-microphone noise reduction and dereverberation techniques are developed. In Part I we present a Generalised Singular Value Decomposition (GSVD) based optimal filtering technique for enhancing multi-microphone speech signals which are degraded by additive coloured noise. Several techniques are presented for reducing the computational complexity and we show that the GSVD-based optimal filtering technique can be integrated into a `Generalised Sidelobe Canceller' type structure. Simulations show that the GSVD-based optimal filtering technique achieves a larger signal-to-noise ratio improvement than standard fixed and adaptive beamforming techniques and ...

Doclo, Simon — Katholieke Universiteit Leuven


Preserving binaural cues in noise reduction algorithms for hearing aids

Hearing aid users experience great difficulty in understanding speech in noisy environments. This has led to the introduction of noise reduction algorithms in hearing aids. The development of these algorithms is typically done monaurally. However, the human auditory system is a binaural system, which compares and combines the signals received by both ears to perceive a sound source as a single entity in space. Providing two monaural, independently operating, noise reduction systems, i.e. a bilateral configuration, to the hearing aid user may disrupt binaural information, needed to localize sound sources correctly and to improve speech perception in noise. In this research project, we first examined the influence of commercially available, bilateral, noise reduction algorithms on binaural hearing. Extensive objective and perceptual evaluations showed that the bilateral adaptive directional microphone (ADM) and the bilateral fixed directional microphone, two of the most ...

Van den Bogaert, Tim — Katholieke Universiteit Leuven


Design and evaluation of digital signal processing algorithms for acoustic feedback and echo cancellation

This thesis deals with several open problems in acoustic echo cancellation and acoustic feedback control. Our main goal has been to develop solutions that provide a high performance and sound quality, and behave in a robust way in realistic conditions. This can be achieved by departing from the traditional ad-hoc methods, and instead deriving theoretically well-founded solutions, based on results from parameter estimation and system identification. In the development of these solutions, the computational efficiency has permanently been taken into account as a design constraint, in that the complexity increase compared to the state-of-the-art solutions should not exceed 50 % of the original complexity. In the context of acoustic echo cancellation, we have investigated the problems of double-talk robustness, acoustic echo path undermodeling, and poor excitation. The two former problems have been tackled by including adaptive decorrelation filters in the ...

van Waterschoot, Toon — Katholieke Universiteit Leuven


Integrated active noise control and noise reduction in hearing aids

In every day life conversations and listening scenarios the desired speech signal is rarely delivered alone. The listener most commonly faces a scenario where he has to understand speech in a noisy environment. Hearing impairments, and more particularly sensorineural losses, can cause a reduction of speech understanding in noise. Therefore, in a hearing aid compensating for such kind of losses it is not sufficient to just amplify the incoming sound. Hearing aids also need to integrate algorithms that allow to discriminate between speech and noise in order to extract a desired speech from a noisy environment. A standard noise reduction scheme in general aims at maximising the signal-to-noise ratio of the signal to be fed in the hearing aid loudspeaker. This signal, however, does not reach the eardrum directly. It first has to propagate through an acoustic path and encounter ...

Serizel, Romain — KU Leuven


Subband and Frequency-Domain Adaptive Filtering Techniques for Speech Enhancement in Hands-free Communication

The telecommunications sector is characterized by an increasing demand for user-friendliness and interactivity. This explains the growing interest in hands-free communication systems. Signal quality in current hands-free systems is unsatisfactory. To overcome this, advanced signal processing techniques such as the subband and frequency-domain adaptive filter are employed to enhance the signal. These techniques are known to have computationally efficient solutions. Furthermore, thanks to the frequency-dependent processing and adaptivity, highly time-varying systems and signals with a continuously changing spectral content such as speech can be handled. This thesis deals with subband and frequency-domain adaptive filtering techniques for speech enhancement in hands-free communication. The text consists of four parts. In the first part design methods for perfect and nearly perfect reconstruction DFT modulated filter banks are discussed. Part II deals with subband and frequency-domain adaptive filtering. The subband adaptive filter and the ...

Eneman, Koen — Katholieke Universiteit Leuven


Adaptive filtering algorithms for acoustic echo and noise cancellation

In this thesis, we develop a number of algorithms for acoustic echo and noise cancellation. We derive a fast exact implementation for the affine projection algorithm (APA), and we also show that when using strong regularization the existing (approximating) fast techniques exhibit problems. We develop a number of algorithms for noise cancellation based on optimal filtering techniques for multi-microphone systems. By using QR-decomposition based techniques, a complexity reduction of a factor 50 to 100 is achieved compared to existing implementations. Finally, we show that instead of using a cascade of a noise-cancellation system and an echo-cancellation system, it is better to solve the combined problem as a global optimization problem. The aforementioned noise reduction techniques can be used to solve this optimization problem.

Rombouts, Geert — Katholieke Universiteit Leuven


Signal processing algorithms for wireless acoustic sensor networks

Recent academic developments have initiated a paradigm shift in the way spatial sensor data can be acquired. Traditional localized and regularly arranged sensor arrays are replaced by sensor nodes that are randomly distributed over the entire spatial field, and which communicate with each other or with a master node through wireless communication links. Together, these nodes form a so-called ‘wireless sensor network’ (WSN). Each node of a WSN has a local sensor array and a signal processing unit to perform computations on the acquired data. The advantage of WSNs compared to traditional (wired) sensor arrays, is that many more sensors can be used that physically cover the full spatial field, which typically yields more variety (and thus more information) in the signals. It is likely that future data acquisition, control and physical monitoring, will heavily rely on this type of ...

Bertrand, Alexander — Katholieke Universiteit Leuven


Adaptive filtering algorithms for acoustic echo cancellation and acoustic feedback control in speech communication applications

Multimedia consumer electronics are nowadays everywhere from teleconferencing, hands-free communications, in-car communications to smart TV applications and more. We are living in a world of telecommunication where ideal scenarios for implementing these applications are hard to find. Instead, practical implementations typically bring many problems associated to each real-life scenario. This thesis mainly focuses on two of these problems, namely, acoustic echo and acoustic feedback. On the one hand, acoustic echo cancellation (AEC) is widely used in mobile and hands-free telephony where the existence of echoes degrades the intelligibility and listening comfort. On the other hand, acoustic feedback limits the maximum amplification that can be applied in, e.g., in-car communications or in conferencing systems, before howling due to instability, appears. Even though AEC and acoustic feedback cancellation (AFC) are functional in many applications, there are still open issues. This means that ...

Gil-Cacho, Jose Manuel — KU Leuven


Distributed Signal Processing Algorithms for Multi-Task Wireless Acoustic Sensor Networks

Recent technological advances in analogue and digital electronics as well as in hardware miniaturization have taken wireless sensing devices to another level by introducing low-power communication protocols, improved digital signal processing capabilities and compact sensors. When these devices perform a certain pre-defined signal processing task such as the estimation or detection of phenomena of interest, a cooperative scheme through wireless connections can significantly enhance the overall performance, especially in adverse conditions. The resulting network consisting of such connected devices (or nodes) is referred to as a wireless sensor network (WSN). In acoustical applications (e.g., speech enhancement) a variant of WSNs, called wireless acoustic sensor networks (WASNs) can be employed in which the sensing unit at each node consists of a single microphone or a microphone array. The nodes of such a WASN can then cooperate to perform a multi-channel acoustic ...

Hassani, Amin — KU Leuven


Broadband adaptive beamforming with low complexity and frequency invariant response

This thesis proposes different methods to reduce the computational complexity as well as increasing the adaptation rate of adaptive broadband beamformers. This is performed exemplarily for the generalised sidelobe canceller (GSC) structure. The GSC is an alternative implementation of the linearly constrained minimum variance beamformer, which can utilise well-known adaptive filtering algorithms, such as the least mean square (LMS) or the recursive least squares (RLS) to perform unconstrained adaptive optimisation. A direct DFT implementation, by which broadband signals are decomposed into frequency bins and processed by independent narrowband beamforming algorithms, is thought to be computationally optimum. However, this setup fail to converge to the time domain minimum mean square error (MMSE) if signal components are not aligned to frequency bins, resulting in a large worst case error. To mitigate this problem of the so-called independent frequency bin (IFB) processor, overlap-save ...

Koh, Choo Leng — University of Southampton


Dereverberation and noise reduction techniques based on acoustic multi-channel equalization

In many hands-free speech communication applications such as teleconferencing or voice-controlled applications, the recorded microphone signals do not only contain the desired speech signal, but also attenuated and delayed copies of the desired speech signal due to reverberation as well as additive background noise. Reverberation and background noise cause a signal degradation which can impair speech intelligibility and decrease the performance for many signal processing techniques. Acoustic multi-channel equalization techniques, which aim at inverting or reshaping the measured or estimated room impulse responses between the speech source and the microphone array, comprise an attractive approach to speech dereverberation since in theory perfect dereverberation can be achieved. However in practice, such techniques suffer from several drawbacks, such as uncontrolled perceptual effects, sensitivity to perturbations in the measured or estimated room impulse responses, and background noise amplification. The aim of this thesis ...

Kodrasi, Ina — University of Oldenburg


Distributed Signal Processing Algorithms for Acoustic Sensor Networks

In recent years, there has been a proliferation of wireless devices for individual use to the point of being ubiquitous. Recent trends have been incorporating many of these devices (or nodes) together, which acquire signals and work in unison over wireless channels, in order to accomplish a predefined task. This type of cooperative sensing and communication between devices form the basis of a so-called wireless sensor network (WSN). Due to the ever increasing processing power of these nodes, WSNs are being assigned more complicated and computationally demanding tasks. Recent research has started to exploit this increased processing power in order for the WSNs to perform tasks pertaining to audio signal acquisition and processing forming so-called wireless acoustic sensor networks (WASNs). Audio signal processing poses new and unique problems when compared to traditional sensing applications as the signals observed often have ...

Szurley, Joseph — KU Leuven

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