Adaptive inverse filtering of room acoustics

Equalization techniques for high order, multichannel, FIR systems are important for dereverberation of speech observed in reverberation using multiple microphones. In this case the multichannel system represents the room impulse responses (RIRs). The existence of near-common zeros in multichannel RIRs can slow down the convergence rate of adaptive inverse filtering algorithms. In this paper, the effect of common and near-common zeros on both the closed-form and the adaptive inverse filtering algorithms is studied. An adaptive shortening algorithm of room acoustics is presented based on this study. 1

Sparsity Based Formulations For Dereverberation

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2016Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2016Konser, konferans, toplantı gibi ortamlarda kaydedilen akustik işaretler, kaydın alındığı ortam nedeni ile yankıya ve gürültüye maruz kalır. Kaynak işaretinin elde edilen gözlemlerden kestirimi yankı giderme problemi olarak isimlendirilir. Bu kayıtlarda göze çarpan yankı etkileri bir süzgeç olarak zaman tanım bölgesinde modellenebilir. Yankı etkilerini modelleyen bu süzgeç oda darbe cevabı olarak isimlendirilir. Oda darbe cevabının bilindiği durumda problem gözü kapalı olmayan yankı giderme problemine dönüşür. Tez boyunca oda darbe cevabının bilindiği durumlar dikkate alınmıştır. Gözlemlenebilir ki, oda darbe cevabı kaynak ve gözlem noktalarına çok bağımlıdır. Bu nedenle oda darbe cevabının bütün uzaydaki noktalar için kestirimi çok zordur. Bu durumda oda darbe cevapları tezdeki deneylerde sentetik olarak uygulanmış veya gözlem ortamında kayıt alındığı sırada gözlemden elde edilmişlerdir. Bölüm 5, bu duruma farklı bir açıdan bakılmasının örneğidir. Bu bölümde oda darbe cevabının kısmen bilindiği ve gözlem ortamı için tek bir süzgeç tanımlanabileceği durumları göz önüne alınmıştır.Acoustic signals recorded in concerts, meetings or conferences are effected by the room impulse response and noise. Estimating the clean source signals from the observations is referred as the dereverberation problem. If the room impulse responses are known, the problem is non-blind dereverberation problem. In this thesis non-blind dereverberation problem is posed using convex penalty functions, with a convex minimization procedure. The convex minimization problems are solved using iterative methods. Through the thesis sparse nature of the time frequency spectrum is referred. In order to transform the time domain signal to a time frequency spectrum Short Time Fourier Transform is used.Yüksek LisansM.Sc

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

System Identification with Applications in Speech Enhancement

As the increasing popularity of integrating hands-free telephony on mobile portable devices and the rapid development of voice over internet protocol, identification of acoustic systems has become desirable for compensating distortions introduced to speech signals during transmission, and hence enhancing the speech quality. The objective of this research is to develop system identification algorithms for speech enhancement applications including network echo cancellation and speech dereverberation. A supervised adaptive algorithm for sparse system identification is developed for network echo cancellation. Based on the framework of selective-tap updating scheme on the normalized least mean squares algorithm, the MMax and sparse partial update tap-selection strategies are exploited in the frequency domain to achieve fast convergence performance with low computational complexity. Through demonstrating how the sparseness of the network impulse response varies in the transformed domain, the multidelay filtering structure is incorporated to reduce the algorithmic delay. Blind identification of SIMO acoustic systems for speech dereverberation in the presence of common zeros is then investigated. First, the problem of common zeros is defined and extended to include the presence of near-common zeros. Two clustering algorithms are developed to quantify the number of these zeros so as to facilitate the study of their effect on blind system identification and speech dereverberation. To mitigate such effect, two algorithms are developed where the two-stage algorithm based on channel decomposition identifies common and non-common zeros sequentially; and the forced spectral diversity approach combines spectral shaping filters and channel undermodelling for deriving a modified system that leads to an improved dereverberation performance. Additionally, a solution to the scale factor ambiguity problem in subband-based blind system identification is developed, which motivates further research on subbandbased dereverberation techniques. Comprehensive simulations and discussions demonstrate the effectiveness of the aforementioned algorithms. A discussion on possible directions of prospective research on system identification techniques concludes this thesis