211 research outputs found
A Zero-Shot Physics-Informed Dictionary Learning Approach for Sound Field Reconstruction
No full textSound field reconstruction aims to estimate pressure fields in areas lacking direct measurements. Existing techniques often rely on strong assumptions or face challenges related to data availability or the explicit modeling of physical properties. To bridge these gaps, this study introduces a zero-shot, physics-informed dictionary learning approach to perform sound field reconstruction. Our method relies only on a few sparse measurements to learn a dictionary, without the need for additional training data. Moreover, by enforcing the Helmholtz equation during the optimization process, the proposed approach ensures that the reconstructed sound field is represented as a linear combination of a few physically meaningful atoms. Evaluations on real-world data show that our approach achieves comparable performance to state-of-the-art dictionary learning techniques, with the advantage of requiring only a few observations of the sound field and no training on a dataset
Replication Data for: Speech enhancement using ego-noise references with a microphone array embedded in an unmanned aerial vehicle
No full textThis dataset contains experimental audio recordings performed with a microphone array embedded in an unmanned aerial vehicle (UAV) in a semi-anechoic chamber used for testing the implemented methods described in the related publication. Please read the README.txt for further description and instructions
Characterization of the Intelligibility of Vowel–Consonant–Vowel (VCV) Recordings in Five Languages for Application in Speech-in-Noise Screening in Multilingual Settings
No full textThe purpose of this study is to characterize the intelligibility of a corpus of Vowel–Consonant–Vowel (VCV) stimuli recorded in five languages (English, French, German, Italian and Portuguese) in order to identify a subset of stimuli for screening individuals of unknown language during speech-in-noise tests. The intelligibility of VCV stimuli was estimated by combining the psychometric functions derived from the Short-Time Objective Intelligibility (STOI) measure with those derived from listening tests. To compensate for the potential increase in speech recognition effort in non-native listeners, stimuli were selected based on three criteria: (i) higher intelligibility; (ii) lower variability of intelligibility; and (iii) shallower psychometric function. The observed intelligibility estimates show that the three criteria for application in multilingual settings were fulfilled by the set of VCVs in English (average intelligibility from 1% to 8% higher; SRT from 4.01 to 2.04 dB SNR lower; average variability up to four times lower; slope from 0.35 to 0.68%/dB SNR lower). Further research is needed to characterize the intelligibility of these stimuli in a large sample of non-native listeners with varying degrees of hearing loss and to determine the possible effects of hearing loss and native language on VCV recognition
Meerkanaals spraakverbetering: Een integratie van A priori en data-afhankelijke ruimtelijke informatie
No full textA speech signal captured by multiple microphones is often subject to a reduced intelligibility and quality due to the presence of noise and room acoustic interferences. Multi-microphone speech enhancement systems therefore aim at the suppression or cancellation of such undesired signals without substantial distortion of the speech signal. A fundamental aspect to the design of several multi-microphone speech enhancement systems is that of the spatial information which relates each microphone signal to the desired speech source. This spatial information is unknown in practice and has to be somehow estimated. Under certain conditions, however, the estimated spatial information can be inaccurate, which subsequently degrades the performance of a multi-microphone speech enhancement system.
This doctoral dissertation is focused on the development and evaluation of acoustic signal processing algorithms in order to address this issue. Specifically, as opposed to conventional means of estimating spatial information using only a priori knowledge or only observable microphone data, an integrated approach is pursued where both a priori and data-dependent spatial information are explicitly used. An initial investigation into such an a approach is firstly considered for the case of a microphone array from a confidence-based perspective, where a confidence metric is used to optimally combine a priori and data-dependent spatial information. The remainder of the dissertation is then dedicated to the study of a microphone array that has access to one or more external microphones. For this microphone configuration, a geometrically-based integration is investigated for the tasks of noise reduction, binaural speech enhancement, and speech dereverberation, where a priori spatial information is used for the microphone array(s) and data-dependent spatial information estimated from the observable microphone data is used for the external microphone(s). A final conception of an integrated approach is then explored for this microphone configuration by merging the confidence-based and geometrically-based integration techniques.
The mathematical framework for the integrated approach as applied to the different microphone configurations is presented, along with experimental evaluation using recorded audio data from various acoustic environments. The results have shown that by following an integrated approach, more spatially robust speech enhancement algorithms can be designed as opposed to relying solely on a priori spatial information or only data-dependent spatial information. Furthermore, the advantage of using a priori spatial knowledge was demonstrated as it served to provide contingency spatial information in cases when the data-dependent spatial information was deemed to be inaccurate. A number of experiments involving an assistive hearing device linked with external microphones have also shown that the proposed speech enhancement algorithms can improve speech intelligibility in comparison to only using the assistive hearing device or only listening to an external microphone signal.status: Publishe
DCASE 2018, Task 5: Monitoring of domestic activities based on multi-channel acoustics - Evaluation dataset
No full text<p>The dataset is a derivative of the SINS dataset and is meant to be used as an evaluation set for the <a href="http://dcase.community/challenge2018/task-monitoring-domestic-activities">DCASE2018 Task 5 challenge</a>. The development set to be used can be found <a href="https://zenodo.org/record/1247102#.WzIF_NUzZhE">here</a>. The dataset is a derivative of the SINS database.</p>
<p>The SINS database contains a continuous recording of one person living in a vacation home over a period of one week. The recordings were manually annotated on daily activity level: "Cooking", "Dishwashing", "Eating", "Social activity (visit, phone call)", "Vacuum cleaning", "Watching TV", "Working", "Presence" and "Absence". More information can be found on (please cite this papers when using the dataset):</p>
<p>G. Dekkers, S. Lauwereins, B. Thoen, M. W. Adhana, H. Brouckxon, T. van Waterschoot, B. Vanrumste, M. Verhelst, and P. Karsmakers, “The SINS database for detection of daily activities in a home environment using an acoustic<br>
sensor network,” in Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 Workshop (DCASE2017), Munich, Germany, November 2017, pp. 32–36.</p>
<p>G. Dekkers, L. Vuegen, T. van Waterschoot, B. Vanrumste, and P. Karsmakers, “DCASE 2018 Challenge - Task 5: Monitoring of domestic activities based on multi-channel acoustics,” KU Leuven, Tech. Rep., July 2018.</p>
<p>The derivative of the SINS database, 'DCASE 2018 – Task 5 evaluation dataset' consists of data collected by 7 microphone arrays in the combined living room and kitchen area. The continuous recordings were split into audio segments of 10s. These audio segments are provided as individual files. In total 72972 segments are made available, leading to approximately 200 hours of data. Ground truth will be made available after the challenge results have been made public. Additionally, a filename mapping will be made available that will map the filenames to a filename similar as the development dataset.</p>
<p>More information about the challenge and the specific dataset can be found here. Information solely related to the content of the dataset is available in 'DCASE2018-task5-eval.doc.zip'.</p>
<p>By accessing or using this database, the user accepts the provided EULA (available in DCASE2018-task5-eval.doc.zip).</p>
Ontwerp en evaluatie van algoritmes voor feedbackbeheersing in implanteerbare hoortoestellen
No full textUsing 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. Nowadays, fully digital sound processors are the norm and this allows the use of advanced algorithms to tackle the different issues a hearing device might have to compensate for. Examples of algorithms implemented in a sound processor are, among others, noise reduction, nonlinear compression, sound scene classification, binaural enhancement, and, most importantly for the scope of this thesis, feedback cancellation.
In a hearing device, feedback arises when a coupling exists between the output (i.e. the loudspeaker or a different kind of actuator) and the input (i.e. the microphone). Feedback in hearing devices gives rise to different kinds of acoustic artifacts and sound degradation which can perceptually be very annoying. Therefore, several approaches to tackle this problem have been proposed. With the advent of digital hearing devices, approaches attempting to reduce feedback through adaptive algorithms have become more viable and are, nowadays, widespread. However, despite the advances of the recent years, the feedback problem in hearing devices has not yet been solved. This is due to different reasons such as, among others, the existence of different classes and kinds of hearing devices requiring specific algorithmic tailoring, the presence of strong power constraints requiring low-complexity algorithms, and the great flexibility requirements a feedback control algorithm must have in order to cope with different daily life activities and soundscapes.
This thesis presents three different tasks related to the development of a feedback control strategy for a novel hearing device as follows: 1) the feedback characterization in two novel hearing devices; 2) the presentation of new algorithms for feedback control and their comparison with the state of the art; 3) the subjective and objective evaluation of the developed algorithms in terms of sound quality
The introductory chapter provides a brief description of the auditory system and of the concept of hearing loss. Subsequently, the main differences between six classes of hearing devices are explained. Finally, an account of the feedback problem in hearing devices is given by discriminating between feedback in conventional HAs and feedback in implantable hearing devices.
The first part of this thesis describes the data collection and the analysis of a series of feedback characterization measurements for two novel implantable hearing devices, the Cochlear™ Codacs™ DACI and an early prototype of a bone conduction implant concept (BCIC). The measurements have been performed on fresh frozen cadaver heads and are used to investigate different important aspects of the feedback these two implants may experience, such as specimen-dependent behaviors, nonlinearities, and effects of structure-borne mechanical versus acoustic feedback.
The second part of this thesis introduces and describes two novel adaptive feedback cancellation (AFC) algorithms providing either comparable or better performance than existing algorithms, and both based on the prediction-error method (PEM) method. The first is an all-frequency-domain method, i.e. the frequency-domain prediction-error-method-based adaptive filter (FD-PEMAF), relying solely on frequency-domain signal-processing operations. The second is a PEM-based AFC algorithm replacing the standard adaptive filter with a simplified Kalman filter, i.e. the PEM-based frequency-domain Kalman filter (PEM-FDKF).
The third part of this thesis describes a study based on a subjective listening test to assess the sound-quality degradation caused by different AFC algorithms, showing a lower sound-quality degradation compared to existing algorithms, introduced by the PEM-FDKF. Additionally, the subjective listening test results are compared to the sound quality predicted by a batch of different
objective measures.
Finally, the contributions of this thesis are reiterated and possible future research directions are explored.status: Publishe
Distributed estimation and equalization of room acoustics in a wireless acoustic sensor network
No full textIn this paper, the use of a wireless acoustic sensor network (WASN) for the estimation and equalization of room acoustics is proposed as a flexible and promising alternative to the traditional wired implementations. We consider a multiple-point equalization problem based on a common-acoustical-pole (CAP) room model. Instead of collecting microphone signals in a central processing unit to compute the CAP model estimate in a centralized fashion, we deploy a large number of autonomous nodes with local sensing, processing, and communication capabilities to solve the CAP model estimation problem in a distributed manner. Even though the WASN nodes are restricted to exchange information with neighboring nodes only, the use of a distributed averaging algorithm results in a CAP model estimate with an accuracy and equalization performance comparable to a wired implementation. © 2012 EURASIP.sponsorship: T. van Waterschoot is a Postdoctoral Fellow of the Research Founda- tion Flanders (FWOVlaanderen). This research work was carried out at the ESAT Laboratory of KU Leuven, in the frame of KU Leuven Research Council CoE EF/05/006 Optimization in Engineering (OPTEC) and PFV/10/002 (OPTEC), Concerted Research Action GOA-MaNet, the Belgian Programme on Interuniversity Attraction Poles initiated by the Belgian Federal Science Policy Office IUAP P6/04 Dynamical systems, control and optimization (DYSCO) 20072011, Research Project IBBT, and Research Project FWO nr. G.0600.08 Signal processing and network design for wireless acoustic sensor networks. The scientific responsibility is assumed by its authors. (KU Leuven Research Council|CoE EF/05/006, OPTEC|PFV/10/002, Belgian Federal Science Policy Office|IUAP P6/04, IBBT, FWO|G.0600.08)status: Publishe
Computational Analysis of a Fast Algorithm for High-order Sparse Linear Prediction
No full textsponsorship: The work of T. L. Jensen is supported by The Danish Council for Independent Research, Technology and Production Sciences, grant number 4005-00122. The work of T. van Waterschoot is supported by the KU Leuven Impulse Fund, grant number IMP/14/037. (Danish Council for Independent Research, Technology and Production Sciences|4005-00122, KU Leuven Impulse Fund|IMP/14/037)status: Publishe
Efficiënte parametrische modellering, identificatie en egalisatie van ruimteakoestiek
No full textThis thesis addresses the fundamental question in room acoustic signal processing concerning the appropriateness of different parametric models for room acoustics.
In order to improve the perceived sound quality, room acoustic 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 tasks.
The main goal of this thesis is then to develop accurate yet efficient parametric models for room acoustics, based on recent advances in system identification and numerical optimization, and on the physical understanding of room acoustics. Orthonormal basis functions (OBF) models are investigated, whose properties, such as orthogonality and scalability, are exploited in the development of iterative flexible algorithms, providing a significant reduction in the number of parameters compared to conventional parametric models.
Improvements were obtained also in the room acoustic system identification framework using OBF adaptive filters, which present interesting properties in terms of error performance and convergence of the filter coefficients. A scalable iterative approach is adopted for the pole estimation, providing a reduction in the filter order, thus helping in addressing some of the issues encountered in RASE applications, such as echo path undermodeling in acoustic echo cancellation, or frequency allocation in inverse filtering for digital equalization.
Particular attention is addressed to the low-frequency region of modal resonances, where the acoustics of small rooms is typically more problematic. In this regard, the issues of measuring RIRs at low frequencies, mostly related to high ambient noise and to the nonlinear distortions produced by the subwoofer, are addressed and a novel procedure for estimating the frequency-dependent reverberation time is suggested. Finally, an effective automatic procedure for the design of a low-complexity parametric equalizer for loudspeaker/room response equalization is proposed, and guidelines for the implementation of an existing solution for nonminimum-phase multi-channel equalization of car cabin acoustics are given.status: Publishe
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