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 ...

Room acoustic signal enhancement (RASE) applications, such as digital equalization, acoustic echo and feedback cancellation, which are commonly found in communication devices and audio equipment, aim at processing the acoustic signals with the final goal of improving the perceived sound quality in rooms. In order to do so, signal processing algorithms require the acoustic response of the room to be represented by means of parametric models and to be identified from the input and output signals of the room acoustic system. In particular, a good model should be both accurate, thus capturing those features of room acoustics that are physically and perceptually most relevant, and efficient, so that it can be implemented as a digital filter and used in practical signal processing tasks. This thesis addresses the fundamental question in room acoustic signal processing concerning the appropriateness of different parametric ...

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 ...

Modern devices such as mobile phones, tablets or smart speakers are commonly equipped with several loudspeakers and microphones. If, for instance, one employs such a device for hands-free communication applications, the signals that are reproduced by the loudspeakers are propagated through the room and are inevitably acquired by the microphones. If no processing is applied, the participants in the far-end room receive delayed reverberated replicas of their own voice, which strongly degrades both speech intelligibility and user comfort. In order to prevent that so-called acoustic echoes are transmitted back to the far-end room, acoustic echo cancelers are commonly employed. The latter make use of adaptive filtering techniques to identify the propagation paths between loudspeakers and microphones. The estimated propagation paths are then employed to compute acoustic echo estimates, which are finally subtracted from the signals acquired by the microphones. In ...

Using a hearing device is one of the most successful approaches to partially restore the degraded functionality of an impaired auditory system. However, due to the complex structure of the human auditory system, hearing impairment can manifest itself in different ways and, therefore, its compensation can be achieved through different classes of hearing devices. Although the majority of hearing devices consists of conventional hearing aids (HAs), several other classes of hearing devices have been developed. For instance, bone-conduction devices (BCDs) and cochlear implants (CIs) have successfully been used for more than thirty years. More recently, other classes of implantable devices have been developed such as middle ear implants (MEIs), implantable BCDs, and direct acoustic cochlear implants (DACIs). Most of these different classes of hearing devices rely on a sound processor running different algorithms able to compensate for the hearing impairment. ...

Modern speech communications are evolving towards a new direction which involves users in a more perceptive way. That is the immersive experience, which may be considered as the “last mile” problem of telecommunications. One of the main feature of immersive communications is the distant-talking, i.e. the hands-free (in the broad sense) speech communications without bodyworn or tethered microphones that takes place in a multisource environment where interfering signals may degrade the communication quality and the intelligibility of the desired speech source. In order to preserve speech quality intelligent acoustic interfaces may be used. An intelligent acoustic interface may comprise multiple microphones and loudspeakers and its peculiarity is to model the acoustic channel in order to adapt to user requirements and to environment conditions. This is the reason why intelligent acoustic interfaces are based on adaptive filtering algorithms. The acoustic path ...

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 ...

Given the widespread use of miniaturized audio interfaces, echo control systems are faced with increasing challenges to address a large variety of acoustic conditions observed by such interfaces. This motivates the use of sophisticated machine learning-based techniques to overcome the limitations of conventional methods. The contributions in this thesis can be outlined by decomposing the task of nonlinear acoustic echo control into two subtasks: Nonlinear Acoustic Echo Cancellation (NAEC) and Acoustic Echo Suppression (AES). In particular, by formulating the single-channel NAEC model-adaptation task as a Bayesian recursive filtering problem, an evolutionary resampling strategy for particle filtering is proposed. The resulting Elitist Resampling Particle Filter (ERPF) is shown experimentally to be an efficient and high-performing approach that can be extended to address challenging conditions such as non-stationary interferers. The fundamental problem of nonlinear model design is addressed by proposing a novel ...

Modern modulation methods as used in 3rd generation mobile communications (UMTS) generate strongly fluctuating transmission signal envelopes with high peak-to-average power ratios. These properties result in significant distortion due to the nonlinear behavior of the radio-frequency power amplifier (RF PA). We propose different nonlinear model structures for such amplifiers, based on memory polynomials and frequency-domain Volterra kernel expansion, where we can reduce the number of free parameters by 80% compared to traditional Volterra series approaches. Because these nonlinear models incorporate memory, we are able to model the nonlinear distortion of RF PAs with sufficient accuracy (e.g., −30 dB relative modeling error ), including the wideband case (bandwidth B = 20 MHz as needed for four-carrier WCDMA). Furthermore, we propose a method to construct RF PA models from frequency-dependent AM/AM and AM/PM conversions. For the compensation of the nonlinearities, we analyze ...

Recently emerging techniques like wave field synthesis (WFS) or Higher-Order Ambisonics (HOA) allow for high-quality spatial audio reproduction, which makes them candidates for the audio reproduction in future telepresence systems or interactive gaming environments with acoustic human-machine interfaces. In such scenarios, acoustic echo cancellation (AEC) will generally be necessary to remove the loudspeaker echoes in the recorded microphone signals before further processing. Moreover, the reproduction quality of WFS or HOA can be improved by adaptive pre-equalization of the loudspeaker signals, as facilitated by listening room equalization (LRE). However, AEC and LRE require adaptive filters, where the large number of reproduction channels of WFS and HOA imply major computational and algorithmic challenges for the implementation of adaptive filters. A technique called wave-domain adaptive filtering (WDAF) promises to master these challenges. However, known literature is still far away from providing sufficient insight ...

Understanding speech in noise and the occurrence of acoustic feedback belong to the major problems of current hearing aid users. Hence, an urgent demand exists for efficient and well-working digital signal processing algorithms that offer a solution to these issues. In this thesis we develop adaptive filtering techniques for noise reduction and acoustic feedback cancellation. Thanks to the availability of low power digital signal processors, these algorithms can be integrated in a hearing aid. Because of the ongoing miniaturization in the hearing aid industry and the growing tendency towards multi-microphone hearing aids, robustness against imperfections such as microphone mismatch, has become a major issue in the design of a noise reduction algorithm. In this thesis we propose multimicrophone noise reduction techniques that are based on multi-channel Wiener filtering (MWF). Theoretical and experimental analysis demonstrate that these MWF-based techniques are less ...

When providing the necessary amplification in hearing aids, the risk of acoustic feedback is increased due to the coupling between the hearing aid loudspeaker and the hearing aid microphone(s). This acoustic feedback is often perceived as an annoying whistling or howling. Thus, to reduce the occurrence of acoustic feedback, robust and fast-acting feedback suppression algorithms are required. The main objective of this thesis is to develop and evaluate algorithms for robust and fast-acting feedback suppression in hearing aids. Specifically, we focus on enhancing the performance of adaptive filtering algorithms that estimate the feedback component in the hearing aid microphone by reducing the number of required adaptive filter coefficients and by improving the trade-off between fast convergence and good steady-state performance. Additionally, we develop fixed spatial filter design methods that can be applied in a multi-microphone earpiece.

Compensating or reducing the nonlinear distortion - usually resulting from a nonlinear system - is becoming an essential requirement in many areas. In this thesis adaptive digital predistortion techniques for a wide class of nonlinear systems are presented. For estimating the coefficients of the predistorter, different learning architectures are considered: the Direct Learning Architecture (DLA) and Indirect Learning Architecture (ILA). In the DLA approach, we propose a new adaptation algorithm - the Nonlinear Filtered-x Prediction Error Method (NFxPEM) algorithm, which has much faster convergence and much better performance compared to the conventional Nonlinear Filtered-x Least Mean Squares (NFxLMS) algorithm. All of these time domain adaptive algorithms require accurate system identification of the nonlinear system. In order to relax or avoid this strict requirement, the NFxLMS with Initial Subsystem Estimates (NFxLMS-ISE) and NFxPEM-ISE algorithms are proposed. Furthermore, we propose a frequency ...

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 ...

Noise or interference is often assumed to be a random process. Conventional linear filtering, control or prediction techniques are used to cancel or reduce the noise. However, some noise processes have been shown to be nonlinear and deterministic. These nonlinear deterministic noise processes appear to be random when analysed with second order statistics. As nonlinear processes are widespread in nature it may be beneficial to exploit the coherence of the nonlinear deterministic noise with nonlinear filtering techniques. The nonlinear deterministic noise processes used in this thesis are generated from nonlinear difference or differential equations which are derived from real world scenarios. Analysis tools from the theory of nonlinear dynamics are used to determine an appropriate sampling rate of the nonlinear deterministic noise processes and their embedding dimensions. Nonlinear models, such as the Volterra series filter and the radial basis function ...