Adaptive Filtered-x Algorithms for Room Equalization Based on Block-Based Combination Schemes

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.[EN] Room equalization has become essential for sound reproduction systems to provide the listener with the desired acoustical sensation. Recently, adaptive filters have been proposed as an effective tool in the core of these systems. In this context, this paper introduces different novel schemes based on the combination of adaptive filters idea: a versatile and flexible approach that permits obtaining adaptive schemes combining the capabilities of several independent adaptive filters. In this way, we have investigated the advantages of a scheme called combination of block-based adaptive filters which allows a blockwise combination splitting the adaptive filters into nonoverlapping blocks. This idea was previously applied to the plant identification problem, but has to be properly modified to obtain a suitable behavior in the equalization application. Moreover, we propose a scheme with the aim of further improving the equalization performance using the a priori knowledge of the energy distribution of the optimal inverse filter, where the block filters are chosen to fit with the coefficients energy distribution. Furthermore, the biased block-based filter is also introduced as a particular case of the combination scheme, especially suited for low signal-to-noise ratios (SNRs) or sparse scenarios. Although the combined schemes can be employed with any kind of adaptive filter, we employ the filtered-x improved proportionate normalized least mean square algorithm as basis of the proposed algorithms, allowing to introduce a novel combination scheme based on partitioned block schemes where different blocks of the adaptive filter use different parameter settings. Several experiments are included to evaluate the proposed algorithms in terms of convergence speed and steady-state behavior for different degrees of sparseness and SNRs.The work of L. A. Azpicueta-Ruiz was supported in part by the Comtmidad de Madrid through CASI-CAM-CM under Grant S2013/ICE-2845, in part by the Spanish Ministry of Economy and Competitiveness through DAMA under Grant TIN2015-70308-REDT, and Grant TEC2014-52289-R, and in part by the European Union. The work of L. Fuster, M. Ferrer, and M. de Diego was supported in part by EU together with the Spanish Government under Grant TEC2015-67387-C4-1-R (MINECO/FEDER), and in part by the Cieneralitat Valenciana under Grant PROMETEOII/2014/003. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Simon Dodo.Fuster Criado, L.; Diego Antón, MD.; Azpicueta-Ruiz, LA.; Ferrer Contreras, M. (2016). Adaptive Filtered-x Algorithms for Room Equalization Based on Block-Based Combination Schemes. IEEE/ACM Transactions on Audio, Speech and Language Processing. 24(10):1732-1745. https://doi.org/10.1109/TASLP.2016.2583065S17321745241

Linear and nonlinear room compensation of audio rendering systems

[EN] Common audio systems are designed with the intent of creating real and immersive scenarios that allow the user to experience a particular acoustic sensation that does not depend on the room he is perceiving the sound. However, acoustic devices and multichannel rendering systems working inside a room, can impair the global audio effect and thus the 3D spatial sound. In order to preserve the spatial sound characteristics of multichannel rendering techniques, adaptive filtering schemes are presented in this dissertation to compensate these electroacoustic effects and to achieve the immersive sensation of the desired acoustic system. Adaptive filtering offers a solution to the room equalization problem that is doubly interesting. First of all, it iteratively solves the room inversion problem, which can become computationally complex to obtain when direct methods are used. Secondly, the use of adaptive filters allows to follow the time-varying room conditions. In this regard, adaptive equalization (AE) filters try to cancel the echoes due to the room effects. In this work, we consider this problem and propose effective and robust linear schemes to solve this equalization problem by using adaptive filters. To do this, different adaptive filtering schemes are introduced in the AE context. These filtering schemes are based on three strategies previously introduced in the literature: the convex combination of filters, the biasing of the filter weights and the block-based filtering. More specifically, and motivated by the sparse nature of the acoustic impulse response and its corresponding optimal inverse filter, we introduce different adaptive equalization algorithms. In addition, since audio immersive systems usually require the use of multiple transducers, the multichannel adaptive equalization problem should be also taken into account when new single-channel approaches are presented, in the sense that they can be straightforwardly extended to the multichannel case. On the other hand, when dealing with audio devices, consideration must be given to the nonlinearities of the system in order to properly equalize the electroacoustic system. For that purpose, we propose a novel nonlinear filtered-x approach to compensate both room reverberation and nonlinear distortion with memory caused by the amplifier and loudspeaker devices. Finally, it is important to validate the algorithms proposed in a real-time implementation. Thus, some initial research results demonstrate that an adaptive equalizer can be used to compensate room distortions.[ES] Los sistemas de audio actuales están diseñados con la idea de crear escenarios reales e inmersivos que permitan al usuario experimentar determinadas sensaciones acústicas que no dependan de la sala o situación donde se esté percibiendo el sonido. Sin embargo, los dispositivos acústicos y los sistemas multicanal funcionando dentro de salas, pueden perjudicar el efecto global sonoro y de esta forma, el sonido espacial 3D. Para poder preservar las características espaciales sonoras de los sistemas de reproducción multicanal, en esta tesis se presentan los esquemas de filtrado adaptativo para compensar dichos efectos electroacústicos y conseguir la sensación inmersiva del sistema sonoro deseado. El filtrado adaptativo ofrece una solución al problema de salas que es interesante por dos motivos. Por un lado, resuelve de forma iterativa el problema de inversión de salas, que puede llegar a ser computacionalmente costoso para los métodos de inversión directos existentes. Por otro lado, el uso de filtros adaptativos permite seguir las variaciones cambiantes de los efectos de la sala de escucha. A este respecto, los filtros de ecualización adaptativa (AE) intentan cancelar los ecos introducidos por la sala de escucha. En esta tesis se considera este problema y se proponen esquemas lineales efectivos y robustos para resolver el problema de ecualización mediante filtros adaptativos. Para conseguirlo, se introducen diferentes esquemas de filtrado adaptativo para AE. Estos esquemas de filtrado se basan en tres estrategias ya usadas en la literatura: la combinación convexa de filtros, el sesgado de los coeficientes del filtro y el filtrado basado en bloques. Más especificamente y motivado por la naturaleza dispersiva de las respuestas al impulso acústicas y de sus correspondientes filtros inversos óptimos, se presentan diversos algoritmos adaptativos de ecualización específicos. Además, ya que los sistemas de audio inmersivos requieren usar normalmente múltiples trasductores, se debe considerar también el problema de ecualización multicanal adaptativa cuando se diseñan nuevas estrategias de filtrado adaptativo para sistemas monocanal, ya que éstas deben ser fácilmente extrapolables al caso multicanal. Por otro lado, cuando se utilizan dispositivos acústicos, se debe considerar la existencia de no linearidades en el sistema elactroacústico, para poder ecualizarlo correctamente. Por este motivo, se propone un nuevo modelo no lineal de filtrado-x que compense a la vez la reverberación introducida por la sala y la distorsión no lineal con memoria provocada por el amplificador y el altavoz. Por último, es importante validar los algoritmos propuestos mediante implementaciones en tiempo real, para asegurarnos que pueden realizarse. Para ello, se presentan algunos resultados experimentales iniciales que muestran la idoneidad de la ecualización adaptativa en problemas de compensación de salas.[CA] Els sistemes d'àudio actuals es dissenyen amb l'objectiu de crear ambients reals i immersius que permeten a l'usuari experimentar una sensació acústica particular que no depèn de la sala on està percebent el so. No obstant això, els dispositius acústics i els sistemes de renderització multicanal treballant dins d'una sala poden arribar a modificar l'efecte global de l'àudio i per tant, l'efecte 3D del so a l'espai. Amb l'objectiu de conservar les característiques espacials del so obtingut amb tècniques de renderització multicanal, aquesta tesi doctoral presenta esquemes de filtrat adaptatiu per a compensar aquests efectes electroacústics i aconseguir una sensació immersiva del sistema acústic desitjat. El filtrat adaptatiu presenta una solució al problema d'equalització de sales que es interessant baix dos punts de vista. Per una banda, el filtrat adaptatiu resol de forma iterativa el problema inversió de sales, que pot arribar a ser molt complexe computacionalment quan s'utilitzen mètodes directes. Per altra banda, l'ús de filtres adaptatius permet fer un seguiment de les condicions canviants de la sala amb el temps. Més concretament, els filtres d'equalització adaptatius (EA) intenten cancel·lar els ecos produïts per la sala. A aquesta tesi, considerem aquest problema i proposem esquemes lineals efectius i robustos per a resoldre aquest problema d'equalització mitjançant filtres adaptatius. Per aconseguir-ho, diferent esquemes de filtrat adaptatiu es presenten dins del context del problema d'EA. Aquests esquemes de filtrat es basen en tres estratègies ja presentades a l'estat de l'art: la combinació convexa de filtres, el sesgat dels pesos del filtre i el filtrat basat en blocs. Més concretament, i motivat per la naturalesa dispersa de la resposta a l'impuls acústica i el corresponent filtre òptim invers, presentem diferents algorismes d'equalització adaptativa. A més a més, com que els sistemes d'àudio immersiu normalment requereixen l'ús de múltiples transductors, cal considerar també el problema d'equalització adaptativa multicanal quan es presenten noves solucions de canal simple, ja que aquestes s'han de poder estendre fàcilment al cas multicanal. Un altre aspecte a considerar quan es treballa amb dispositius d'àudio és el de les no linealitats del sistema a l'hora d'equalitzar correctament el sistema electroacústic. Amb aquest objectiu, a aquesta tesi es proposa una nova tècnica basada en filtrat-x no lineal, per a compensar tant la reverberació de la sala com la distorsió no lineal amb memòria introduïda per l'amplificador i els altaveus. Per últim, és important validar la implementació en temps real dels algorismes proposats. Amb aquest objectiu, alguns resultats inicials demostren la idoneïtat de l'equalització adaptativa en problemes de compensació de sales.Fuster Criado, L. (2015). Linear and nonlinear room compensation of audio rendering systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/5945

Combinations of adaptive filters

Adaptive filters are at the core of many signal processing applications, ranging from acoustic noise supression to echo cancelation [1], array beamforming [2], channel equalization [3], to more recent sensor network applications in surveillance, target localization, and tracking. A trending approach in this direction is to recur to in-network distributed processing in which individual nodes implement adaptation rules and diffuse their estimation to the network [4], [5].The work of Jerónimo Arenas-García and Luis Azpicueta-Ruiz was partially supported by the Spanish Ministry of Economy and Competitiveness (under projects TEC2011-22480 and PRI-PIBIN-2011-1266. The work of Magno M.T. Silva was partially supported by CNPq under Grant 304275/2014-0 and by FAPESP under Grant 2012/24835-1. The work of Vítor H. Nascimento was partially supported by CNPq under grant 306268/2014-0 and FAPESP under grant 2014/04256-2. The work of Ali Sayed was supported in part by NSF grants CCF-1011918 and ECCS-1407712. We are grateful to the colleagues with whom we have shared discussions and coauthorship of papers along this research line, especially Prof. Aníbal R. Figueiras-Vidal

Adaptive algorithms and structures with potential application in reverberation time estimation in occupied rooms

Realistic and accurate room reverberation time (RT) extraction is very important in room acoustics. Occupied room RT extraction is even more attractive but it is technically challenging, since the presence of the audience changes the room acoustics. Recently, some methods have been proposed to solve the occupied room RT extraction problem by utilizing passively received speech signals, such as the maximum likelihood estimation (MLE) technique and the artificial neural network (ANN) scheme. Although reasonable RT estimates can be extracted by these methods, noise may affect their accuracy, especially for occupied rooms, where noise is inevitable due to the presence of the audience. To improve the accuracy of the RT estimates from high noise occupied rooms, adaptive techniques are utilized in this thesis as a preprocess ing stage for RT estimation. As a demonstration, this preprocessing together with the MLE method will be applied to extract the RT of a room in which there is significant noise from passively received speech signals. This preprocessing can also be potentially used to aid in the extraction of other acoustic parameters, such as the early decay time (EDT) and speech transmission index (STI). The motivation of the proposed approach is to utilize adaptive techniques, namely blind source separation (BSS) and adaptive noise cancellation (ANC), based upon the least mean square (LMS) algorithm, to reduce the noise level contained in the received speech signal, so that the RT extracted from the signal output generated by the preprocessing can be more accurate. Further research is also performed on some fundamental topics re lated to adaptive techniques. The first topic is variable step size LMS (VSSLMS) algorithms, which are designed to enhance the convergence rate of the LMS algorithm. The concept of gradient based VSSLMS algorithms is described, and new gradient based VSSLMS algorithms are proposed for applications where the input signal is statistically stationary and the signal-to-noise ratio (SNR) is zero decibels or less. The second topic is variable tap-length LMS (VTLMS) algorithms. VTLMS algorithms are designed for applications where the tap-length of the adaptive filter coefficient vector is unknown. The target of these algorithms is to establish a good steady-state tap-length for the LMS algorithm. A steady-state performance analysis for a VTLMS algorithm, the fractional tap-length (FT) algorithm is therefore provided. To improve the performance of the FT algorithm in high noise conditions, a convex combination approach for the FT algorithm is proposed. Furthermore, a new practical VTLMS algorithm is also designed for applications in which the optimal filter has an exponential decay impulse response, commonplace in enclosed acoustic environments. These original research outputs provide deep understanding of the VTLMS algorithms. Finally, the idea of variable tap-length is introduced for the first time into the BSS algorithm. Similar to the FT algorithm, the tap-length of the natural gradient (NG) algorithm, which is one of the most important sequential BSS algorithms is also made variable rather than fixed. A new variable tap-length NG algorithm is proposed to search for a steady-state adaptive filter vector tap-length, and thereby provide a good compromise between steady-state performance and computational complexity. The research recorded in this thesis gives a first step in introducing adaptive techniques into acoustic parameter extraction. Limited by the performance of such adaptive techniques, only simulated studies and comparisons are performed to evaluate the proposed new approach. With further development of the associated adaptive techniques, practical applications of the proposed approach may be obtained in the future.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A room acoustics measurement system using non-invasive microphone arrays

This thesis summarises research into adaptive room correction for small rooms and pre-recorded material, for example music of films. A measurement system to predict the sound at a remote location within a room, without a microphone at that location was investigated. This would allow the sound within a room to be adaptively manipulated to ensure that all listeners received optimum sound, therefore increasing their enjoyment. The solution presented used small microphone arrays, mounted on the room's walls. A unique geometry and processing system was designed, incorporating three processing stages, temporal, spatial and spectral. The temporal processing identifies individual reflection arrival times from the recorded data. Spatial processing estimates the angles of arrival of the reflections so that the three-dimensional coordinates of the reflections' origin can be calculated. The spectral processing then estimates the frequency response of the reflection. These estimates allow a mathematical model of the room to be calculated, based on the acoustic measurements made in the actual room. The model can then be used to predict the sound at different locations within the room. A simulated model of a room was produced to allow fast development of algorithms. Measurements in real rooms were then conducted and analysed to verify the theoretical models developed and to aid further development of the system. Results from these measurements and simulations, for each processing stage are presented

Adaptive algorithms and structures with potential application in reverberation time estimation in occupied rooms

Realistic and accurate room reverberation time (RT) extraction is very important in room acoustics. Occupied room RT extraction is even more attractive but it is technically challenging, since the presence of the audience changes the room acoustics. Recently, some methods have been proposed to solve the occupied room RT extraction problem by utilizing passively received speech signals, such as the maximum likelihood estimation (MLE) technique and the artificial neural network (ANN) scheme. Although reasonable RT estimates can be extracted by these methods, noise may affect their accuracy, especially for occupied rooms, where noise is inevitable due to the presence of the audience. To improve the accuracy of the RT estimates from high noise occupied rooms, adaptive techniques are utilized in this thesis as a preprocess ing stage for RT estimation. As a demonstration, this preprocessing together with the MLE method will be applied to extract the RT of a room in which there is significant noise from passively received speech signals. This preprocessing can also be potentially used to aid in the extraction of other acoustic parameters, such as the early decay time (EDT) and speech transmission index (STI). The motivation of the proposed approach is to utilize adaptive techniques, namely blind source separation (BSS) and adaptive noise cancellation (ANC), based upon the least mean square (LMS) algorithm, to reduce the noise level contained in the received speech signal, so that the RT extracted from the signal output generated by the preprocessing can be more accurate. Further research is also performed on some fundamental topics re lated to adaptive techniques. The first topic is variable step size LMS (VSSLMS) algorithms, which are designed to enhance the convergence rate of the LMS algorithm. The concept of gradient based VSSLMS algorithms is described, and new gradient based VSSLMS algorithms are proposed for applications where the input signal is statistically stationary and the signal-to-noise ratio (SNR) is zero decibels or less. The second topic is variable tap-length LMS (VTLMS) algorithms. VTLMS algorithms are designed for applications where the tap-length of the adaptive filter coefficient vector is unknown. The target of these algorithms is to establish a good steady-state tap-length for the LMS algorithm. A steady-state performance analysis for a VTLMS algorithm, the fractional tap-length (FT) algorithm is therefore provided. To improve the performance of the FT algorithm in high noise conditions, a convex combination approach for the FT algorithm is proposed. Furthermore, a new practical VTLMS algorithm is also designed for applications in which the optimal filter has an exponential decay impulse response, commonplace in enclosed acoustic environments. These original research outputs provide deep understanding of the VTLMS algorithms. Finally, the idea of variable tap-length is introduced for the first time into the BSS algorithm. Similar to the FT algorithm, the tap-length of the natural gradient (NG) algorithm, which is one of the most important sequential BSS algorithms is also made variable rather than fixed. A new variable tap-length NG algorithm is proposed to search for a steady-state adaptive filter vector tap-length, and thereby provide a good compromise between steady-state performance and computational complexity. The research recorded in this thesis gives a first step in introducing adaptive techniques into acoustic parameter extraction. Limited by the performance of such adaptive techniques, only simulated studies and comparisons are performed to evaluate the proposed new approach. With further development of the associated adaptive techniques, practical applications of the proposed approach may be obtained in the future

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