In many speech communication applications, such as hands-free telephony and hearing aids, the microphones are located at a distance from the speaker. Therefore, in addition to the desired speech signal, the microphone signals typically contain undesired reverberation and noise, caused by acoustic reflections and undesired sound sources. Since these disturbances tend to degrade the quality of speech communication, decrease speech intelligibility and negatively affect speech recognition, efficient dereverberation and denoising methods are required. This thesis deals with blind dereverberation methods, not requiring any knowledge about the room impulse responses between the speaker and the microphones. More specifically, we propose a general framework for blind speech dereverberation based on multi-channel linear prediction (MCLP) and exploiting sparsity of the speech signal in the time-frequency domain.

Reverberation is the sum of reflected sound waves and is present in any conventional room. Speech communication devices such as mobile phones in hands-free mode, tablets, smart TVs, teleconferencing systems, hearing aids, voice-controlled systems, etc. use one or more microphones to pick up the desired speech signals. When the microphones are not in the proximity of the desired source, strong reverberation and noise can degrade the signal quality at the microphones and can impair the intelligibility and the performance of automatic speech recognizers. Therefore, it is a highly demanded task to process the microphone signals such that reverberation and noise are reduced. The process of reducing or removing reverberation from recorded signals is called dereverberation. As dereverberation is usually a completely blind problem, where the only available information are the microphone signals, and as the acoustic scenario can be non-stationary, ...

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 ...

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 ...

Reverberation consists of a complex acoustic phenomenon that occurs inside rooms. Many audio signal processing methods, addressing source localization, signal enhancement and other tasks, often assume absence of reverberation. Consequently, reverberant environments are considered challenging as state-ofthe-art methods can perform poorly. The acoustics of a room can be described using a variety of mathematical models, among which, physical models are the most complete and accurate. The use of physical models in audio signal processing methods is often non-trivial since it can lead to ill-posed inverse problems. These inverse problems require proper regularization to achieve meaningful results and involve the solution of computationally intensive large-scale optimization problems. Recently, however, sparse regularization has been applied successfully to inverse problems arising in different scientific areas. The increased computational power of modern computers and the development of new efficient optimization algorithms makes it possible ...

Due to their decreased ability to understand speech hearing impaired may have difficulties to interact in social groups, especially when several people are talking simultaneously. Fortunately, in the last decades hearing aids have evolved from simple sound amplifiers to modern digital devices with complex functionalities including noise reduction algorithms, which are crucial to improve speech understanding in background noise for hearing-impaired persons. Since many hearing aid users are fitted with two hearing aids, so-called binaural hearing aids have been developed, which exchange data and signals through a wireless link such that the processing in both hearing aids can be synchronized. In addition to reducing noise and limiting speech distortion, another important objective of noise reduction algorithms in binaural hearing aids is the preservation of the listener’s impression of the acoustical scene, in order to exploit the binaural hearing advantage and ...

In most real-world acoustical scenarios, speech signals captured by distant microphones from a source are reverberated due to multipath propagation, and the reverberation may impair speech intelligibility. Speech dereverberation can be achieved by equalizing the channels from the source to microphones. Equalization systems can be computed using estimates of multichannel acoustic impulse responses. However, the estimates obtained from system identification always include errors; the fact that an equalization system is able to equalize the estimated multichannel acoustic system does not mean that it is able to equalize the true system. The objective of this thesis is to propose and investigate robust equalization methods for multichannel acoustic systems in the presence of system identification errors. Equalization systems can be computed using the multiple-input/output inverse theorem or multichannel least-squares method. However, equalization systems obtained from these methods are very sensitive to system ...

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 ...

In many speech applications such as hands-free telephony or voice-controlled home assistants, the distance between the user and the recording microphones can be relatively large. In such a far-field scenario, the recorded microphone signals are typically corrupted by noise and reverberation, which may severely degrade the performance of speech recognition systems and reduce intelligibility and quality of speech in communication applications. In order to limit these effects, speech enhancement algorithms are typically applied. The main objective of this thesis is to develop novel speech enhancement algorithms for noisy and reverberant environments and signal-based measures to evaluate these algorithms, focusing on solutions that are applicable in realistic scenarios. First, we propose a single-channel speech enhancement algorithm for joint noise and reverberation reduction. The proposed algorithm uses a spectral gain to enhance the input signal, where the gain is computed using a ...

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 ...

The advent of multi-microphone setups on a plethora of commercial devices in recent years has generated a newfound interest in the development of robust microphone array signal processing methods. These methods are generally used to either estimate parameters associated with acoustic scene or to extract signal(s) of interest. In most practical scenarios, the sources are located in the far-field of a microphone array where the main spatial information of interest is the direction-of-arrival (DOA) of the plane waves originating from the source positions. The focus of this thesis is to incorporate robustness against either lack of or imperfect/erroneous information regarding the DOAs of the sound sources within a microphone array signal processing framework. The DOAs of sound sources is by itself important information, however, it is most often used as a parameter for a subsequent processing method. One of the ...

Never before has speech been captured as often by electronic devices equipped with one or multiple microphones, serving a variety of applications. It is the key aspect in digital telephony, hearing devices, and voice-driven human-to-machine interaction. When speech is recorded, the microphones also capture a variety of further, undesired sound components due to adverse acoustic conditions. Interfering speech, background noise and reverberation, i.e. the persistence of sound in a room after excitation caused by a multitude of reflections on the room enclosure, are detrimental to the quality and intelligibility of target speech as well as the performance of automatic speech recognition. Hence, speech enhancement aiming at estimating the early target-speech component, which contains the direct component and early reflections, is crucial to nearly all speech-related applications presently available. In this thesis, we compare, propose and evaluate existing and novel approaches ...

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 ...

In modern devices which provide hands-free speech capturing functionality, such as hands-free communication kits and voice-controlled devices, the received speech signal at the microphones is corrupted by background noise, interfering speech signals, and room reverberation. In many practical situations, the microphones are not necessarily located near the desired source, and hence, the ratio of the desired speech power to the power of the background noise, the interfering speech, and the reverberation at the microphones can be very low, often around or even below 0 dB. In such situations, the comfort of human-to-human communication, as well as the accuracy of automatic speech recognisers for voice-controlled applications can be signi cantly degraded. Therefore, e ffective speech enhancement algorithms are required to process the microphone signals before transmitting them to the far-end side for communication, or before feeding them into a speech recognition ...

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 ...