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 everyday speech communication situations undesired acoustic sources, such as competing speakers and background noise, frequently lead to a decreased speech intelligibility. Over the last decades, hearing devices have evolved from simple sound amplification devices to more sophisticated devices with complex functionalities such as multi-microphone speech enhancement. Binaural beamforming algorithms are spatial filters that exploit the information captured by multiple microphones on both sides of the head of the listener. Besides reducing the undesired sources, another important objective of a binaural beamforming algorithm is the preservation of the binaural cues of all sound sources to preserve the listener's spatial impression of the acoustic scene. The aim of this thesis is to develop and evaluate advanced binaural beamforming algorithms and to incorporate one or more external microphones in a binaural hearing device configuration. The first focus is to improve state-of-the-art binaural ...

One in five experiences hearing loss. The World Health Organization estimates that this number will increase to one in four in 2050. Luckily, effective hearing devices such as hearing aids and cochlear implants exist with advanced speaker enhancement algorithms that can significantly improve the quality of life of people suffering from hearing loss. State-of-the-art hearing devices, however, underperform in a so-called `cocktail party' scenario, when multiple persons are talking simultaneously (such as at a family dinner or reception). In such a situation, the hearing device does not know which speaker the user intends to attend to and thus which speaker to enhance and which other ones to suppress. Therefore, a new problem arises in cocktail party problems: determining which speaker a user is attending to, referred to as the auditory attention decoding (AAD) problem. The problem of selecting the attended ...

The problem of segregating a sound source of interest from an acoustic background has been extensively studied due to applications in hearing prostheses, robust speech/speaker recognition and audio information retrieval. Computational auditory scene analysis (CASA) approaches the segregation problem by utilizing grouping cues involved in the perceptual organization of sound by human listeners. Binaural processing, where input signals resemble those that enter the two ears, is of particular interest in the CASA field. The dominant approach to binaural segregation has been to derive spatially selective filters in order to enhance the signal in a direction of interest. As such, the problems of sound localization and sound segregation are closely tied. While spatial filtering has been widely utilized, substantial performance degradation is incurred in reverberant environments and more fundamentally, segregation cannot be performed without sufficient spatial separation between sources. This dissertation ...

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 ...

A large part of human speech communication takes place in noisy environments and is supported by technical devices. For example, a hearing-impaired person might use a hearing aid to take part in a conversation in a busy restaurant. These devices, but also telecommunication in noisy environments or voiced-controlled assistants, make use of speech enhancement and separation algorithms that improve the quality and intelligibility of speech by separating speakers and suppressing background noise as well as other unwanted effects such as reverberation. If the devices are equipped with more than one microphone, which is very common nowadays, then multi-channel speech enhancement approaches can leverage spatial information in addition to single-channel tempo-spectral information to perform the task. Traditionally, linear spatial filters, so-called beamformers, have been employed to suppress the signal components from other than the target direction and thereby enhance the desired ...

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 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 ...

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 ...

In the modern world, we are increasingly surrounded by computation devices with communication links and one or more microphones. Such devices are, for example, smartphones, tablets, laptops or hearing aids. These devices can work together as nodes in an acoustic sensor network (ASN). Such networks are a growing platform that opens the possibility for many practical applications. ASN based speech enhancement, source localization, and event detection can be applied for teleconferencing, camera control, automation, or assisted living. For this kind of applications, the awareness of auditory objects and their spatial positioning are key properties. In order to provide these two kinds of information, novel methods have been developed in this thesis. Information on the type of auditory objects is provided by a novel real-time sound classification method. Information on the position of human speakers is provided by a novel localization ...

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 ...

Sound source localization algorithms have a long research history in the field of digital signal processing. Many common applications like intelligent personal assistants, teleconferencing systems and methods for technical diagnosis in acoustics require an accurate localization of sound sources in the environment. However, dynamic environments entail a particular challenge for these systems. For instance, voice controlled smart home applications, where the speaker, as well as potential noise sources, are moving within the room, are a typical example of dynamic environments. Classical sound source localization systems only have limited capabilities to deal with dynamic acoustic scenarios. In this thesis, three novel approaches to sound source localization that extend existing classical methods will be presented. The first system is proposed in the context of audiovisual source localization. Determining the position of sound sources in adverse acoustic conditions can be improved by including ...

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 the world of Information and communications technology (ICT), strategies for innovation and development are increasingly focusing on applications that require spatial representation and real-time interaction with and within 3D-media environments. One of the major challenges that such applications have to address is user-centricity, reflecting e.g. on developing complexity-hiding services so that people can personalize their own delivery of services. In these terms, multimodal interfaces represent a key factor for enabling an inclusive use of new technologies by everyone. In order to achieve this, multimodal realistic models that describe our environment are needed, and in particular models that accurately describe the acoustics of the environment and communication through the auditory modality are required. Examples of currently active research directions and application areas include 3DTV and future internet, 3D visual-sound scene coding, transmission and reconstruction and teleconferencing systems, to name but ...

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 ...