Spatial, Spectral, and Perceptual Nonlinear Noise Reduction for Hands-free Microphones in a Car

Speech enhancement in an automobile is a challenging problem because interference can come from engine noise, fans, music, wind, road noise, reverberation, echo, and passengers engaging in other conversations. Hands-free microphones make the situation worse because the strength of the desired speech signal reduces with increased distance between the microphone and talker. Automobile safety is improved when the driver can use a hands-free interface to phones and other devices instead of taking his eyes off the road. The demand for high quality hands-free communication in the automobile requires the introduction of more powerful algorithms. This thesis shows that a unique combination of five algorithms can achieve superior speech enhancement for a hands-free system when compared to beamforming or spectral subtraction alone. Several different designs were analyzed and tested before converging on the configuration that achieved the best results. Beamforming, voice activity detection, spectral subtraction, perceptual nonlinear weighting, and talker isolation via pitch tracking all work together in a complementary iterative manner to create a speech enhancement system capable of significantly enhancing real world speech signals. The following conclusions are supported by the simulation results using data recorded in a car and are in strong agreement with theory. Adaptive beamforming, like the Generalized Side-lobe Canceller (GSC), can be effectively used if the filters only adapt during silent data frames because too much of the desired speech is cancelled otherwise. Spectral subtraction removes stationary noise while perceptual weighting prevents the introduction of offensive audible noise artifacts. Talker isolation via pitch tracking can perform better when used after beamforming and spectral subtraction because of the higher accuracy obtained after initial noise removal. Iterating the algorithm once increases the accuracy of the Voice Activity Detection (VAD), which improves the overall performance of the algorithm. Placing the microphone(s) on the ceiling above the head and slightly forward of the desired talker appears to be the best location in an automobile based on the experiments performed in this thesis. Objective speech quality measures show that the algorithm removes a majority of the stationary noise in a hands-free environment of an automobile with relatively minimal speech distortion

A study on wireless hearing aids system configuration and simulation

Master'sMASTER OF SCIENC

Improving speech intelligibility in hearing aids. Part I: Signal processing algorithms

[EN] The improvement of speech intelligibility in hearing aids is a traditional problem that still remains open and unsolved. Modern devices may include signal processing algorithms to improve intelligibility: automatic gain control, automatic environmental classification or speech enhancement. However, the design of such algorithms is strongly restricted by some engineering constraints caused by the reduced dimensions of hearing aid devices. In this paper, we discuss the application of state-of-theart signal processing algorithms to improve speech intelligibility in digital hearing aids, with particular emphasis on speech enhancement algorithms. Different alternatives for both monaural and binaural speech enhancement have been considered, arguing whether they are suitable to be implemented in a commercial hearing aid or not.This work has been funded by the Spanish Ministry of Science and Innovation, under project TEC2012-38142-C04-02.Ayllón, D.; Gil Pita, R.; Rosa Zurera, M.; Padilla, L.; Piñero Sipán, MG.; Diego Antón, MD.; Ferrer Contreras, M.... (2014). Improving speech intelligibility in hearing aids. Part I: Signal processing algorithms. Waves. 6:61-71. http://hdl.handle.net/10251/57901S6171

Beiträge zu breitbandigen Freisprechsystemen und ihrer Evaluation

This work deals with the advancement of wideband hands-free systems (HFS’s) for mono- and stereophonic cases of application. Furthermore, innovative contributions to the corr. field of quality evaluation are made. The proposed HFS approaches are based on frequency-domain adaptive filtering for system identification, making use of Kalman theory and state-space modeling. Functional enhancement modules are developed in this work, which improve one or more of key quality aspects, aiming at not to harm others. In so doing, these modules can be combined in a flexible way, dependent on the needs at hand. The enhanced monophonic HFS is evaluated according to automotive ITU-T recommendations, to prove its customized efficacy. Furthermore, a novel methodology and techn. framework are introduced in this work to improve the prototyping and evaluation process of automotive HF and in-car-communication (ICC) systems. The monophonic HFS in several configurations hereby acts as device under test (DUT) and is thoroughly investigated, which will show the DUT’s satisfying performance, as well as the advantages of the proposed development process. As current methods for the evaluation of HFS’s in dynamic conditions oftentimes still lack flexibility, reproducibility, and accuracy, this work introduces “Car in a Box” (CiaB) as a novel, improved system for this demanding task. It is able to enhance the development process by performing high-resolution system identification of dynamic electro-acoustical systems. The extracted dyn. impulse response trajectories are then applicable to arbitrary input signals in a synthesis operation. A realistic dynamic automotive auralization of a car cabin interior is available for HFS evaluation. It is shown that this system improves evaluation flexibility at guaranteed reproducibility. In addition, the accuracy of evaluation methods can be increased by having access to exact, realistic imp. resp. trajectories acting as a so-called “ground truth” reference. If CiaB is included into an automotive evaluation setup, there is no need for an acoustical car interior prototype to be present at this stage of development. Hency, CiaB may ease the HFS development process. Dynamic acoustic replicas may be provided including an arbitrary number of acoustic car cabin interiors for multiple developers simultaneously. With CiaB, speech enh. system developers therefore have an evaluation environment at hand, which can adequately replace the real environment.Diese Arbeit beschäftigt sich mit der Weiterentwicklung breitbandiger Freisprechsysteme für mono-/stereophone Anwendungsfälle und liefert innovative Beiträge zu deren Qualitätsmessung. Die vorgestellten Verfahren basieren auf im Frequenzbereich adaptierenden Algorithmen zur Systemidentifikation gemäß Kalman-Theorie in einer Zustandsraumdarstellung. Es werden funktionale Erweiterungsmodule dahingehend entwickelt, dass mindestens eine Qualitätsanforderung verbessert wird, ohne andere eklatant zu verletzen. Diese nach Anforderung flexibel kombinierbaren algorithmischen Erweiterungen werden gemäß Empfehlungen der ITU-T (Rec. P.1110/P.1130) in vorwiegend automotiven Testszenarien getestet und somit deren zielgerichtete Wirksamkeit bestätigt. Es wird eine Methodensammlung und ein technisches System zur verbesserten Prototypentwicklung/Evaluation von automotiven Freisprech- und Innenraumkommunikationssystemen vorgestellt und beispielhaft mit dem monophonen Freisprechsystem in diversen Ausbaustufen zur Anwendung gebracht. Daraus entstehende Vorteile im Entwicklungs- und Testprozess von Sprachverbesserungssystem werden dargelegt und messtechnisch verifiziert. Bestehende Messverfahren zum Verhalten von Freisprechsystemen in zeitvarianten Umgebungen zeigten bisher oft nur ein unzureichendes Maß an Flexibilität, Reproduzierbarkeit und Genauigkeit. Daher wird hier das „Car in a Box“-Verfahren (CiaB) entwickelt und vorgestellt, mit dem zeitvariante elektro-akustische Systeme technisch identifiziert werden können. So gewonnene dynamische Impulsantworten können im Labor in einer Syntheseoperation auf beliebige Eingangsignale angewandt werden, um realistische Testsignale unter dyn. Bedingungen zu erzeugen. Bei diesem Vorgehen wird ein hohes Maß an Flexibilität bei garantierter Reproduzierbarkeit erlangt. Es wird gezeigt, dass die Genauigkeit von darauf basierenden Evaluationsverfahren zudem gesteigert werden kann, da mit dem Vorliegen von exakten, realen Impulsantworten zu jedem Zeitpunkt der Messung eine sogenannte „ground truth“ als Referenz zur Verfügung steht. Bei der Einbindung von CiaB in einen Messaufbau für automotive Freisprechsysteme ist es bedeutsam, dass zu diesem Zeitpunkt das eigentliche Fahrzeug nicht mehr benötigt wird. Es wird gezeigt, dass eine dyn. Fahrzeugakustikumgebung, wie sie im Entwicklungsprozess von automotiven Sprachverbesserungsalgorithmen benötigt wird, in beliebiger Anzahl vollständig und mind. gleichwertig durch CiaB ersetzt werden kann

Saw-Less radio receivers in CMOS

Smartphones play an essential role in our daily life. Connected to the internet, we can easily keep in touch with family and friends, even if far away, while ever more apps serve us in numerous ways. To support all of this, higher data rates are needed for ever more wireless users, leading to a very crowded radio frequency spectrum. To achieve high spectrum efficiency while reducing unwanted interference, high-quality band-pass filters are needed. Piezo-electrical Surface Acoustic Wave (SAW) filters are conventionally used for this purpose, but such filters need a dedicated design for each new band, are relatively bulky and also costly compared to integrated circuit chips. Instead, we would like to integrate the filters as part of the entire wireless transceiver with digital smartphone hardware on CMOS chips. The research described in this thesis targets this goal. It has recently been shown that N-path filters based on passive switched-RC circuits can realize high-quality band-select filters on CMOS chips, where the center frequency of the filter is widely tunable by the switching-frequency. As CMOS downscaling following Moore’s law brings us lower clock-switching power, lower switch on-resistance and more compact metal-to-metal capacitors, N-path filters look promising. This thesis targets SAW-less wireless receiver design, exploiting N-path filters. As SAW-filters are extremely linear and selective, it is very challenging to approximate this performance with CMOS N-path filters. The research in this thesis proposes and explores several techniques for extending the linearity and enhancing the selectivity of N-path switched-RC filters and mixers, and explores their application in CMOS receiver chip designs. First the state-of-the-art in N-path filters and mixer-first receivers is reviewed. The requirements on the main receiver path are examined in case SAW-filters are removed or replaced by wideband circulators. The feasibility of a SAW-less Frequency Division Duplex (FDD) radio receiver is explored, targeting extreme linearity and compression Irequirements. A bottom-plate mixing technique with switch sharing is proposed. It improves linearity by keeping both the gate-source and gate-drain voltage swing of the MOSFET-switches rather constant, while halving the switch resistance to reduce voltage swings. A new N-path switch-RC filter stage with floating capacitors and bottom-plate mixer-switches is proposed to achieve very high linearity and a second-order voltage-domain RF-bandpass filter around the LO frequency. Extra out-of-band (OOB) rejection is implemented combined with V-I conversion and zero-IF frequency down-conversion in a second cross-coupled switch-RC N-path stage. It offers a low-ohmic high-linearity current path for out-of-band interferers. A prototype chip fabricated in a 28 nm CMOS technology achieves an in-band IIP3 of +10 dBm , IIP2 of +42 dBm, out-of-band IIP3 of +44 dBm, IIP2 of +90 dBm and blocker 1-dB gain-compression point of +13 dBm for a blocker frequency offset of 80 MHz. At this offset frequency, the measured desensitization is only 0.6 dB for a 0-dBm blocker, and 3.5 dB for a 10-dBm blocker at 0.7 GHz operating frequency (i.e. 6 and 9 dB blocker noise figure). The chip consumes 38-96 mW for operating frequencies of 0.1-2 GHz and occupies an active area of 0.49 mm2. Next, targeting to cover all frequency bands up to 6 GHz and achieving a noise figure lower than 3 dB, a mixer-first receiver with enhanced selectivity and high dynamic range is proposed. Capacitive negative feedback across the baseband amplifier serves as a blocker bypassing path, while an extra capacitive positive feedback path offers further blocker rejection. This combination of feedback paths synthesizes a complex pole pair at the input of the baseband amplifier, which is up-converted to the RF port to obtain steeper RF-bandpass filter roll-off than the conventional up-converted real pole and reduced distortion. This thesis explains the circuit principle and analyzes receiver performance. A prototype chip fabricated in 45 nm Partially Depleted Silicon on Insulator (PDSOI) technology achieves high linearity (in-band IIP3 of +3 dBm, IIP2 of +56 dBm, out-of-band IIP3 = +39 dBm, IIP2 = +88 dB) combined with sub-3 dB noise figure. Desensitization due to a 0-dBm blocker is only 2.2 dB at 1.4 GHz operating frequency. IIFinally, to demonstrate the performance of the implemented blocker-tolerant receiver chip designs, a test setup with a real mobile phone is built to verify the sensitivity of the receiver chip for different practical blocking scenarios

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

Automatic speech recognition: from study to practice

Today, automatic speech recognition (ASR) is widely used for different purposes such as robotics, multimedia, medical and industrial application. Although many researches have been performed in this field in the past decades, there is still a lot of room to work. In order to start working in this area, complete knowledge of ASR systems as well as their weak points and problems is inevitable. Besides that, practical experience improves the theoretical knowledge understanding in a reliable way. Regarding to these facts, in this master thesis, we have first reviewed the principal structure of the standard HMM-based ASR systems from technical point of view. This includes, feature extraction, acoustic modeling, language modeling and decoding. Then, the most significant challenging points in ASR systems is discussed. These challenging points address different internal components characteristics or external agents which affect the ASR systems performance. Furthermore, we have implemented a Spanish language recognizer using HTK toolkit. Finally, two open research lines according to the studies of different sources in the field of ASR has been suggested for future work

An investigation of the utility of monaural sound source separation via nonnegative matrix factorization applied to acoustic echo and reverberation mitigation for hands-free telephony

In this thesis we investigate the applicability and utility of Monaural Sound Source Separation (MSSS) via Nonnegative Matrix Factorization (NMF) for various problems related to audio for hands-free telephony. We first investigate MSSS via NMF as an alternative acoustic echo reduction approach to existing approaches such as Acoustic Echo Cancellation (AEC). To this end, we present the single-channel acoustic echo problem as an MSSS problem, in which the objective is to extract the users signal from a mixture also containing acoustic echo and noise. To perform separation, NMF is used to decompose the near-end microphone signal onto the union of two nonnegative bases in the magnitude Short Time Fourier Transform domain. One of these bases is for the spectral energy of the acoustic echo signal, and is formed from the in- coming far-end user’s speech, while the other basis is for the spectral energy of the near-end speaker, and is trained with speech data a priori. In comparison to AEC, the speaker extraction approach obviates Double-Talk Detection (DTD), and is demonstrated to attain its maximal echo mitigation performance immediately upon initiation and to maintain that performance during and after room changes for similar computational requirements. Speaker extraction is also shown to introduce distortion of the near-end speech signal during double-talk, which is quantified by means of a speech distortion measure and compared to that of AEC. Subsequently, we address Double-Talk Detection (DTD) for block-based AEC algorithms. We propose a novel block-based DTD algorithm that uses the available signals and the estimate of the echo signal that is produced by NMF-based speaker extraction to compute a suitably normalized correlation-based decision variable, which is compared to a fixed threshold to decide on doubletalk. Using a standard evaluation technique, the proposed algorithm is shown to have comparable detection performance to an existing conventional block-based DTD algorithm. It is also demonstrated to inherit the room change insensitivity of speaker extraction, with the proposed DTD algorithm generating minimal false doubletalk indications upon initiation and in response to room changes in comparison to the existing conventional DTD. We also show that this property allows its paired AEC to converge at a rate close to the optimum. Another focus of this thesis is the problem of inverting a single measurement of a non- minimum phase Room Impulse Response (RIR). We describe the process by which percep- tually detrimental all-pass phase distortion arises in reverberant speech filtered by the inverse of the minimum phase component of the RIR; in short, such distortion arises from inverting the magnitude response of the high-Q maximum phase zeros of the RIR. We then propose two novel partial inversion schemes that precisely mitigate this distortion. One of these schemes employs NMF-based MSSS to separate the all-pass phase distortion from the target speech in the magnitude STFT domain, while the other approach modifies the inverse minimum phase filter such that the magnitude response of the maximum phase zeros of the RIR is not fully compensated. Subjective listening tests reveal that the proposed schemes generally produce better quality output speech than a comparable inversion technique