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

Sparseness-controlled adaptive algorithms for supervised and unsupervised system identification

In single-channel hands-free telephony, the acoustic coupling between the loudspeaker and the microphone can be strong and this generates echoes that can degrade user experience. Therefore, effective acoustic echo cancellation (AEC) is necessary to maintain a stable system and hence improve the perceived voice quality of a call. Traditionally, adaptive filters have been deployed in acoustic echo cancellers to estimate the acoustic impulse responses (AIRs) using adaptive algorithms. The performances of a range of well-known algorithms are studied in the context of both AEC and network echo cancellation (NEC). It presents insights into their tracking performances under both time-invariant and time-varying system conditions. In the context of AEC, the level of sparseness in AIRs can vary greatly in a mobile environment. When the response is strongly sparse, convergence of conventional approaches is poor. Drawing on techniques originally developed for NEC, a class of time-domain and a frequency-domain AEC algorithms are proposed that can not only work well in both sparse and dispersive circumstances, but also adapt dynamically to the level of sparseness using a new sparseness-controlled approach. As it will be shown later that the early part of the acoustic echo path is sparse while the late reverberant part of the acoustic path is dispersive, a novel approach to an adaptive filter structure that consists of two time-domain partition blocks is proposed such that different adaptive algorithms can be used for each part. By properly controlling the mixing parameter for the partitioned blocks separately, where the block lengths are controlled adaptively, the proposed partitioned block algorithm works well in both sparse and dispersive time-varying circumstances. A new insight into an analysis on the tracking performance of improved proportionate NLMS (IPNLMS) is presented by deriving the expression for the mean-square error. By employing the framework for both sparse and dispersive time-varying echo paths, this work validates the analytic results in practical simulations for AEC. The time-domain second-order statistic based blind SIMO identification algorithms, which exploit the cross relation method, are investigated and then a technique with proportionate step-size control for both sparse and dispersive system identification is also developed

Computationally efficient implementation of sarse-tap FIR adaptive filters with tap-position control on intel IA-32 processors

金沢大学理工研究域　電子情報学

Computationally efficient implementation of sarse-tap FIR adaptive filters with tap-position control on intel IA-32 processors

金沢大学理工研究域　電子情報学系This paper presents an computationally ef cient implementation of sparse-tap FIR adaptive lters with tapposition control on Intel IA-32 processors with single-instruction multiple-data (SIMD) capability. In order to overcome randomorder memory access which prevents a ectorization, a blockbased processing and a re-ordering buffer are introduced. A dynamic register allocation and the use of memory-to-register operations help the maximization of the loop-unrolling level. Up to 66percent speedup is achieved.Organized by the Electrical Engineering/Electronics, Computer, Telecommunications, and Information Technology Association (ECTI) Co-organized by GCEO-NGIT, Hokkaido University Technical sponsored by IEEE Circuits and Systems Society In cooperation with the Institute of Electronics, Information and Communication Engineering (IEICE

Techniques to Improve the Efficiency of Data Transmission in Cable Networks

The cable television (CATV) networks, since their introduction in the late 1940s, have now become a crucial part of the broadcasting industry. To keep up with growing demands from the subscribers, cable networks nowadays not only provide television programs but also deliver two-way interactive services such as telephone, high-speed Internet and social TV features. A new standard for CATV networks is released every five to six years to satisfy the growing demands from the mass market. From this perspective, this thesis is concerned with three main aspects for the continuing development of cable networks: (i) efficient implementations of backward-compatibility functions from the old standard, (ii) addressing and providing solutions for technically-challenging issues in the current standard and, (iii) looking for prospective features that can be implemented in the future standard. Since 1997, five different versions of the digital CATV standard had been released in North America. A new standard often contains major improvements over the previous one. The latest version of the standard, namely DOCSIS 3.1 (released in late 2013), is packed with state-of-the-art technologies and allows approximately ten times the amount of traffic as compared to the previous standard, DOCSIS 3.0 (released in 2008). Backward-compatibility is a must-have function for cable networks. In particular, to facilitate the system migration from older standards to a newer one, the backward compatible functions in the old standards must remain in the newer-standard products. More importantly, to keep the implementation cost low, the inherited backward compatible functions must be redesigned by taking advantage of the latest technology and algorithms. To improve the backward-compatibility functions, the first contribution of the thesis focuses on redesigning the pulse shaping filter by exploiting infinite impulse response (IIR) filter structures as an alternative to the conventional finite impulse response (FIR) structures. Comprehensive comparisons show that more economical filters with better performance can be obtained by the proposed design algorithm, which considers a hybrid parameterization of the filter's transfer function in combination with a constraint on the pole radius to be less than 1. The second contribution of the thesis is a new fractional timing estimation algorithm based on peak detection by log-domain interpolation. When compared with the commonly-used timing detection method, which is based on parabolic interpolation, the proposed algorithm yields more accurate estimation with a comparable implementation cost. The third contribution of the thesis is a technique to estimate the multipath channel for DOCSIS 3.1 cable networks. DOCSIS 3.1 is markedly different from prior generations of CATV networks in that OFDM/OFDMA is employed to create a spectrally-efficient signal. In order to effectively demodulate such a signal, it is necessary to employ a demodulation circuit which involves estimation and tracking of the multipath channel. The estimation and tracking must be highly accurate because extremely dense constellations such as 4096-QAM and possibly 16384-QAM can be used in DOCSIS 3.1. The conventional OFDM channel estimators available in the literature either do not perform satisfactorily or are not suitable for the DOCSIS 3.1 channel. The novel channel estimation technique proposed in this thesis iteratively searches for parameters of the channel paths. The proposed technique not only substantially enhances the channel estimation accuracy, but also can, at no cost, accurately identify the delay of each echo in the system. The echo delay information is valuable for proactive maintenance of the network. The fourth contribution of this thesis is a novel scheme that allows OFDM transmission without the use of a cyclic prefix (CP). The structure of OFDM in the current DOCSIS 3.1 does not achieve the maximum throughput if the channel has multipath components. The multipath channel causes inter-symbol-interference (ISI), which is commonly mitigated by employing CP. The CP acts as a guard interval that, while successfully protecting the signal from ISI, reduces the transmission throughput. The problem becomes more severe for downstream direction, where the throughput of the entire system is determined by the user with the worst channel. To solve the problem, this thesis proposes major alterations to the current DOCSIS 3.1 OFDM/OFDMA structure. The alterations involve using a pair of Nyquist filters at the transceivers and an efficient time-domain equalizer (TEQ) at the receiver to reduce ISI down to a negligible level without the need of CP. Simulation results demonstrate that, by incorporating the proposed alterations to the DOCSIS 3.1 down-link channel, the system can achieve the maximum throughput over a wide range of multipath channel conditions