Implementation and evaluation of a low complexity microphone array for speaker recognition

Includes bibliographical references (leaves 83-86).This thesis discusses the application of a microphone array employing a noise canceling beamforming technique for improving the robustness of speaker recognition systems in a diffuse noise field

Adaptive Algorithms for Intelligent Acoustic Interfaces

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 modelling entails a set of problems which have to be taken into account in designing an adaptive filtering algorithm. Such problems may be basically generated by a linear or a nonlinear process and can be tackled respectively by linear or nonlinear adaptive algorithms. In this work we consider such modelling problems and we propose novel effective adaptive algorithms that allow acoustic interfaces to be robust against any interfering signals, thus preserving the perceived quality of desired speech signals. As regards linear adaptive algorithms, a class of adaptive filters based on the sparse nature of the acoustic impulse response has been recently proposed. We adopt such class of adaptive filters, named proportionate adaptive filters, and derive a general framework from which it is possible to derive any linear adaptive algorithm. Using such framework we also propose some efficient proportionate adaptive algorithms, expressly designed to tackle problems of a linear nature. On the other side, in order to address problems deriving from a nonlinear process, we propose a novel filtering model which performs a nonlinear transformations by means of functional links. Using such nonlinear model, we propose functional link adaptive filters which provide an efficient solution to the modelling of a nonlinear acoustic channel. Finally, we introduce robust filtering architectures based on adaptive combinations of filters that allow acoustic interfaces to more effectively adapt to environment conditions, thus providing a powerful mean to immersive speech communications

Measuring the Phase Variation of a DOCSIS 3.1 Full Duplex Channel

Including a Full Duplex option into DOCSIS introduces several problems. One of the more troublesome issues is the presence of a strong self interference signal that leaks from the transmit side to the receive side of a cable node. This self interference is caused by echoes in the channel that translate the forward travelling transmit signals into a reverse travelling signal, as well as, by leakage from the hybrid coupler used to couple the upstream and downstream signals. To suppress this self interference an echo canceller is implemented to remove the unwanted interference from the received signal. Unfortunately with the high rates of data transmission used in modern day CATV networks the echo canceller needs tremendous precision. A major concern in the implementation of Full Duplex into DOCSIS is if the channels used are even very slightly time varying. The echos in such channels change with time and can be difficult for the echo canceller to track. Changes in the response of the channel cause the echo profile of the network to shift and the echo canceler to re-adapt to the new channel response. The issue with this changing response is that it is possible for the channel to change faster than the echo canceller can adapt, resulting in the interference becoming unacceptably high. Since the channel is a physical network of coaxial cables often exposed to the environment, its propagation properties can be affected by wind swaying pole mounted cables, or by rapid heating from the sun, or sudden shifts in the load of the network. With information on how the physical properties of the cable changes, the engineers designing the echo canceller can know how fast the canceller must adapt to changes and also have a better measure of how reliable its echo cancellation will be. In this thesis the stability of the echo profile of the channel is measured. It is shown that the property of the channel with the greatest potential to rapidly change and cause noise after echo cancellation is the phase response of the channel. Due to this, the approach of this thesis is to measure the fluctuations in the phase of the channel response of a CATV network constructed in the lab. To measure the fluctuations in the phase response of the channel, a PLL (Phase Locked Loop) based circuit is designed and built on an FPGA (Field Programmable Gate Array) and connected to a model of a simple CATV network. The PLL circuit used to measure the phase fluctuations of the channel is designed to be able to measure changes occurring faster than 0.1 Hz and with a power higher than $10^{-7} \: V^2$. The circuit is able to capture data from the channel over a period of 90 seconds. Using this phase variation measurement circuit a series of experiments were performed on a model CATV DOCSIS network. It was found that many physical disturbances to the network had the effect of rapidly shifting the phase response of the network. Heating the cables in the network was found to shift the phase response upwards of $20000\:\mu$radians. Flexing the cables in the network was found to have a peak phase variation of $8000\: \mu$radians with similar effects found from walking over cables. Overall, it was clear that physical effects on the network had the propensity to rapidly shift the network response. Any echo canceller that is designed in the future will have to consider these effects when reporting the cancellation that it is able to achieve

Adaptive Algorithms for Intelligent Acoustic Interfaces

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 modelling entails a set of problems which have to be taken into account in designing an adaptive filtering algorithm. Such problems may be basically generated by a linear or a nonlinear process and can be tackled respectively by linear or nonlinear adaptive algorithms. In this work we consider such modelling problems and we propose novel effective adaptive algorithms that allow acoustic interfaces to be robust against any interfering signals, thus preserving the perceived quality of desired speech signals. As regards linear adaptive algorithms, a class of adaptive filters based on the sparse nature of the acoustic impulse response has been recently proposed. We adopt such class of adaptive filters, named proportionate adaptive filters, and derive a general framework from which it is possible to derive any linear adaptive algorithm. Using such framework we also propose some efficient proportionate adaptive algorithms, expressly designed to tackle problems of a linear nature. On the other side, in order to address problems deriving from a nonlinear process, we propose a novel filtering model which performs a nonlinear transformations by means of functional links. Using such nonlinear model, we propose functional link adaptive filters which provide an efficient solution to the modelling of a nonlinear acoustic channel. Finally, we introduce robust filtering architectures based on adaptive combinations of filters that allow acoustic interfaces to more effectively adapt to environment conditions, thus providing a powerful mean to immersive speech communications

Single- and multi-microphone speech dereverberation using spectral enhancement

In speech communication systems, such as voice-controlled systems, hands-free mobile telephones, and hearing aids, the received microphone signals are degraded by room reverberation, background noise, and other interferences. This signal degradation may lead to total unintelligibility of the speech and decreases the performance of automatic speech recognition systems. In the context of this work reverberation is the process of multi-path propagation of an acoustic sound from its source to one or more microphones. The received microphone signal generally consists of a direct sound, reflections that arrive shortly after the direct sound (commonly called early reverberation), and reflections that arrive after the early reverberation (commonly called late reverberation). Reverberant speech can be described as sounding distant with noticeable echo and colouration. These detrimental perceptual effects are primarily caused by late reverberation, and generally increase with increasing distance between the source and microphone. Conversely, early reverberations tend to improve the intelligibility of speech. In combination with the direct sound it is sometimes referred to as the early speech component. Reduction of the detrimental effects of reflections is evidently of considerable practical importance, and is the focus of this dissertation. More specifically the dissertation deals with dereverberation techniques, i.e., signal processing techniques to reduce the detrimental effects of reflections. In the dissertation, novel single- and multimicrophone speech dereverberation algorithms are developed that aim at the suppression of late reverberation, i.e., at estimation of the early speech component. This is done via so-called spectral enhancement techniques that require a specific measure of the late reverberant signal. This measure, called spectral variance, can be estimated directly from the received (possibly noisy) reverberant signal(s) using a statistical reverberation model and a limited amount of a priori knowledge about the acoustic channel(s) between the source and the microphone(s). In our work an existing single-channel statistical reverberation model serves as a starting point. The model is characterized by one parameter that depends on the acoustic characteristics of the environment. We show that the spectral variance estimator that is based on this model, can only be used when the source-microphone distance is larger than the so-called critical distance. This is, crudely speaking, the distance where the direct sound power is equal to the total reflective power. A generalization of the statistical reverberation model in which the direct sound is incorporated is developed. This model requires one additional parameter that is related to the ratio between the direct sound energy and the sound energy of all reflections. The generalized model is used to derive a novel spectral variance estimator. When the novel estimator is used for dereverberation rather than the existing estimator, and the source-microphone distance is smaller than the critical distance, the dereverberation performance is significantly increased. Single-microphone systems only exploit the temporal and spectral diversity of the received signal. Reverberation, of course, also induces spatial diversity. To additionally exploit this diversity, multiple microphones must be used, and their outputs must be combined by a suitable spatial processor such as the so-called delay and sum beamformer. It is not a priori evident whether spectral enhancement is best done before or after the spatial processor. For this reason we investigate both possibilities, as well as a merge of the spatial processor and the spectral enhancement technique. An advantage of the latter option is that the spectral variance estimator can be further improved. Our experiments show that the use of multiple microphones affords a significant improvement of the perceptual speech quality. The applicability of the theory developed in this dissertation is demonstrated using a hands-free communication system. Since hands-free systems are often used in a noisy and reverberant environment, the received microphone signal does not only contain the desired signal but also interferences such as room reverberation that is caused by the desired source, background noise, and a far-end echo signal that results from a sound that is produced by the loudspeaker. Usually an acoustic echo canceller is used to cancel the far-end echo. Additionally a post-processor is used to suppress background noise and residual echo, i.e., echo which could not be cancelled by the echo canceller. In this work a novel structure and post-processor for an acoustic echo canceller are developed. The post-processor suppresses late reverberation caused by the desired source, residual echo, and background noise. The late reverberation and late residual echo are estimated using the generalized statistical reverberation model. Experimental results convincingly demonstrate the benefits of the proposed system for suppressing late reverberation, residual echo and background noise. The proposed structure and post-processor have a low computational complexity, a highly modular structure, can be seamlessly integrated into existing hands-free communication systems, and affords a significant increase of the listening comfort and speech intelligibility

Passive radar on moving platforms exploiting DVB-T transmitters of opportunity

The work, effort, and research put into passive radar for stationary receivers have shown significant developments and progress in recent years. The next challenge is mounting a passive radar on moving platforms for the purpose of target detection and ground imaging, e.g. for covert border control. A passive radar on a moving platform has many advantages and offers many benefits, however there is also a considerable drawback that has limited its application so far. Due to the movement the clutter returns are spread in Doppler and may overlap moving targets, which are then difficult to detect. While this problem is common for an active radar as well, with a passive radar a further problem arises: It is impossible to control the exploited time-varying waveform emitted from a telecommunication transmitter. A conventional processing approach is ineffective as the time-varying waveform leads to residuals all over the processed data. Therefore a dedicated clutter cancellation method, e.g. the displaced phase centre antenna (DPCA) approach, does not have the ability to completely remove the clutter, so that target detection is considerably limited. The aim must be therefore to overcome this limitation by exploiting a processing technique, which is able to remove these residuals in order to cope with the clutter returns thus making target detection feasible. The findings of this research and thesis show that a reciprocal filtering based stage is able to provide a time-invariant impulse response similar to the transmissions of an active radar. Due to this benefit it is possible to achieve an overall complete clutter removal together with a dedicated DPCA stage, so that moving target detection is considerably improved, making it possible in the first place. Based on mathematical analysis and on simulations it is proven, that by exploiting this processing in principle an infinite clutter cancellation can be achieved. This result shows that the reciprocal filter is an essential processing stage. Applications on real data acquired from two different measurement campaigns prove these results. By the proposed approach, the limiting factor (i.e. the time-varying waveform) for target detection is negotiated, and in principle any clutter cancellation technique known from active radar can be applied. Therefore this analysis and the results provide a substantial contribution to the passive radar research community and enables it to address the next questions