Andreas Spanias

Perceptual coding of digital audio

During the last decade, CD-quality digital audio has essentially replaced analog audio. Emerging digital audio applications for network, wireless, and multimedia computing systems face a series of constraints such as reduced channel bandwidth, limited storage capacity, and low cost. These new applications have created a demand for high-quality digital audio delivery at low bit rates. In response to this need, considerable research has been devoted to the development of algorithms for perceptually transparent coding of high-fidelity (CD-quality) digital audio. As a result, many algorithms have been proposed, and several have now become international and/or commercial product standards. This paper reviews algorithms for perceptually transparent coding of CD-quality digital audio, including both research and standardization activities. This paper is organized as follows. First, psychoacoustic principles are described, with the MPEG psychoacoustic signal analysis model 1 discussed in some detail. Next, filter bank design issues and algorithms are addressed, with a particular emphasis placed on the modified discrete cosine transform, a perfect reconstruction cosine-modulated filter bank that has become of central importance in perceptual audio coding. Then, we review methodologies that achieve perceptually transparent coding of FM- and CD-quality audio signals, including algorithms that manipulate transform components, subband signal decompositions, sinusoidal signal components, and linear prediction parameters, as well as hybrid algorithms that make use of more than one signal model. These discussions concentrate on architectures and applications of those techniques that utilize psychoacoustic models to exploit efficiently masking characteristics of the human receiver. Several algorithms that have become international and/or commercial standards receive in-depth treatment, including the ISO/IEC MPEG family (-1, -2, -4), the Lucent Technologies PAC/EPAC/MPAC, the Dolby AC-2/AC-3, and the Sony ATRAC/SDDS algorithms. Then, we describe subjective evaluation methodologies in some detail, including the ITU-R BS.1116 recommendation on subjective measurements of small impairments. This paper concludes with a discussion of future research directions.

Smart-antenna systems for mobile communication networks. Part 1. Overview and antenna design

This paper focuses on the interaction and integration of several critical components of a mobile communication network using smart-antenna systems. This wireless network is composed of communicating nodes that are mobile, and its topology is continuously changing. One of the central motivations for this work comes from the observed dependence of the overall network throughput on the design of the adaptive antenna system and its underlying signal processing algorithms. Part 1 of this two-part paper gives a brief overview of smart-antenna systems, including the different types of smart-antenna systems, and the reason for their having gained popularity. Moreover, details of typical antenna array designs suitable for the wireless communication devices are included in this part.

Cepstrum-based pitch detection using a new statistical V/UV classification algorithm

An improved cepstrum-based voicing detection and pitch determination algorithm is presented. Voicing decisions are made using a multifeature voiced/unvoiced classification algorithm based on statistical analysis of cepstral peak, zero-crossing rate, and energy of short-time segments of the speech signal. Pitch frequency information is extracted by a modified cepstrum-based method and then carefully refined using pitch tracking, correction, and smoothing algorithms. Performance analysis on a large database indicates considerable improvement relative to the conventional cepstrum method. The proposed algorithm is also shown to be robust to additive noise.

Smart antenna system analysis, integration and performance for mobile ad-hoc networks (MANETs)

This paper focuses on the interaction and integration of several critical components of a mobile ad-hoc network (MANET) using smart antenna systems. A MANET is a wireless network where the communicating nodes are mobile and the network topology is continuously changing. One of the central motivations for this work comes from the observed dependence of the overall network throughput on the design of the adaptive antenna system and its underlying signal processing algorithms. In fact, a major objective of this work is to study and document the overall efficiency of the network in terms of the antenna pattern and the length of the training sequence used by the beamforming algorithms. This study also considers in sufficient detail problems dealing with the choice of direction of arrival algorithm and the performance of the adaptive beamformer in the presence of antenna coupling effects. Furthermore, the paper presents strategies and algorithms to combat the effects of fading channels on the overall system.

Smart-antenna system for mobile communication networks .Part 2. Beamforming and network throughput

Part 1 of this paper provided an overview of smart-antenna systems, and presented a planar array as a design example. In addition, Part 1 discussed the potential of smart antennas with regard to providing increased capacity in wireless communication networks. Part 2 introduces the signal-processing aspects of the antenna array. In particular, it describes the utility of direction-of-arrival algorithms in array-antenna systems, and gives an overview of the signal-processing algorithms that are used to adapt the antenna radiation pattern. The adaptive-algorithm descriptions are accompanied by simulation results obtained for a specific network topology. In particular, the antenna system is simulated assuming a mobile network topology that is continuously changing. Basic results presented are the dependence of the overall network throughput on the design of the adaptive-antenna system, and on the properties of the adaptive-beamforming algorithms and associated antenna patterns.

A review of algorithms for perceptual coding of digital audio signals

Considerable research has been devoted to the development of algorithms for perceptually transparent coding of high-fidelity (CD-quality) digital audio. As a result, many algorithms have been proposed and several have now become international and/or commercial product standards. This paper reviews algorithms for perceptually transparent coding of CD-quality digital audio, including both research and standardization activities. First, psychoacoustic principles are described with the MPEG psychoacoustic signal analysis model 1 discussed in some detail. Then, we review methodologies which achieve perceptually transparent coding of FM- and CD-quality audio signals, including algorithms which manipulate transform components and subband signal decompositions. The discussion concentrates on architectures and applications of those techniques which utilize psychoacoustic models to exploit efficiently masking characteristics of the human receiver. Several algorithms which have become international and/or commercial standards are also presented, including the ISO/MPEG family and the Dolby AC-3 algorithms. The paper concludes with a brief discussion of future research directions.

Autoregressive modeling and feature analysis of DNA sequences

A parametric signal processing approach for DNA sequence analysis based on autoregressive (AR) modeling is presented. AR model residual errors and AR model parameters are used as features. The AR residual error analysis indicate a high specificity of coding DNA sequences, while AR feature-based analysis helps distinguish between coding and noncoding DNA sequences. An AR model-based string searching algorithm is also proposed. The effect of several types of numerical mapping rules in th proposed method is demonstrated.

Interactive online undergraduate laboratories using J-DSP

An interactive Web-based simulation tool called Java-DSP (J-DSP) for use in digital signal processing (DSP)-related electrical engineering courses is described. J-DSP is an object-oriented simulation environment that enables students and distance learners to perform online signal processing simulations, visualize Web-based interactive demos, and perform computer laboratories from remote locations. J-DSP is accompanied by a series of hands-on laboratory exercises that complement classroom and textbook content. The laboratories cover several fundamental concepts, including z transforms, digital filter design, spectral analysis, multirate signal processing, and statistical signal processing. Online assessment instruments for the evaluation of the J-DSP software and the associated laboratory exercises have been developed. Pre/postassessment data have been collected and analyzed for each laboratory in an effort to assess the impact of the tool on student learning.

High-performance alphabet recognition

Alphabet recognition is needed in many applications for retrieving information associated with the spelling of a name, such as telephone numbers, addresses, etc. This is a difficult recognition task due to the acoustic similarities existing between letters in the alphabet (e.g., the E-set letters). This paper presents the development of a high-performance alphabet recognizer that has been evaluated on studio quality as well as on telephone-bandwidth speech. Unlike previously proposed systems, the alphabet recognizer presented is based on context-dependent phoneme hidden Markov models (HMMs), which have been found to outperform whole-word models by as much as 8%. The proposed recognizer incorporates a series of new approaches to tackle the problems associated with the confusions occurring between the stop consonants in the E-set and the confusions between the nasals (i.e., letters M and N). First, a new feature representation is proposed for improved stop consonant discrimination, and second, two subspace approaches are proposed for improved nasal discrimination. The subspace approach was found to yield a 45% error-rate reduction in nasal discrimination. Various other techniques are also proposed, yielding a 97.3% speaker-independent performance on alphabet recognition and 95% speaker-independent performance on E-set recognition, A telephone alphabet recognizer was also developed using context-dependent HMMs. When tested on the recognition of 300 last names (which are contained in a list of 50,000 common last names) spelled by 300 speakers, the recognizer achieved 91.7% correct letter recognition with 1.1% letter insertions.

Estimation Over Fading Channels With Limited Feedback Using Distributed Sensing

We consider a wireless sensor network for distributed estimation over fading channels. The sensors transmit their observations over a multiple access fading channel to a fusion center (FC), where a source parameter is estimated. The sensor transmissions add incoherently over a multiple access channel, which motivates the need for channel knowledge at the sensors to improve performance. We consider the effects of different fading channel models on the performance of the system, and characterize the effect of different amounts of channel information at the sensors. We calculate the variance of the estimate for cases when both perfect, and differing amounts of partial channel information are available at the sensors. Asymptotic variance expressions for large number of sensors are derived for different channel statistics and feedback scenarios. We show that the degradation in variance due to using only channel phase information is at most a factor of 4/¿ over Rayleigh fading channels. We consider continuous feedback error and evaluate the degradation in performance due to differing degrees of error. The loss in performance due to feedback quantization, and effect of error in feedback are also quantified. We also consider speed of convergence, and compare the rate of convergence under different conditions. Further, we characterize the effect of correlated channels between sensors and the FC, and provide the different values for the speed of convergence for this case. Simulation results are provided to show that only a few tens of sensors are required for the asymptotic results to hold. Numerical results corroborate our analytical results.