A Pattern Recognition Model of Voice-Based Personal Verification Systems for Forensic Applications

Abstract-The success of automatic speaker recognition in laboratory environments suggests applications in forensic science for establishing the Identity of individuals on the basis of features extracted from speech. A theoretical model for such a verification scheme for continuous normaliy distributed featureIss developed. The three cases of using a) single feature, b)multipliendependent measurements of a single feature, and c)multpleindependent features are explored.The number iofndependent features needed for areliable personal identification is computed based on the theoretcal model and an expklatory study of some speech featues.

Non-linear regression model for spatial variation in precipitation chemistry for South India

Chemical composition of rainwater changes from sea to inland under the influence of several major factors - topographic location of area, its distance from sea, annual rainfall. A model is developed here to quantify the variation in precipitation chemistry under the influence of inland distance and rainfall amount. Various sites in India categorized as 'urban', 'suburban' and 'rural' have been considered for model development. pH, HCO3, NO3 and Mg do not change much from coast to inland while, SO4 and Ca change is subjected to local emissions. Cl and Na originate solely from sea salinity and are the chemistry parameters in the model. Non-linear multiple regressions performed for the various categories revealed that both rainfall amount and precipitation chemistry obeyed a power law reduction with distance from sea. Cl and Na decrease rapidly for the first 100 km distance from sea, then decrease marginally for the next 100 km, and later stabilize. Regression parameters estimated for different cases were found to be consistent (R-2 similar to 0.8). Variation in one of the parameters accounted for urbanization. Model was validated using data points from the southern peninsular region of the country. Estimates are found to be within 99.9% confidence interval. Finally, this relationship between the three parameters - rainfall amount, coastline distance, and concentration (in terms of Cl and Na) was validated with experiments conducted in a small experimental watershed in the south-west India. Chemistry estimated using the model was in good correlation with observed values with a relative error of similar to 5%. Monthly variation in the chemistry is predicted from a downscaling model and then compared with the observed data. Hence, the model developed for rain chemistry is useful in estimating the concentrations at different spatio-temporal scales and is especially applicable for south-west region of India. (C) 2008 Elsevier Ltd. All rights reserved.

Integrating voice and data on SALAN: an experimental local area network

This paper is concerned with the integration of voice and data on an experimental local area network used by the School of Automation, of the Indian Institute of Science. SALAN (School of Automation Local Area Network) consists of a number of microprocessor-based communication nodes linked to a shared coaxial cable transmission medium. The communication nodes handle the various low-level functions associated with computer communication, and interface user data equipment to the network. SALAN at present provides a file transfer facility between an Intel Series III microcomputer development system and a Texas Instruments Model 990/4 microcomputer system. Further, a packet voice communication system has also been implemented on SALAN. The various aspects of the design and implementation of the above two utilities are discussed.

An analytical model for performance evaluation of multimedia applications over EDCA in an IEEE 802.11e WLAN

We extend the modeling heuristic of (Harsha et al. 2006. In IEEE IWQoS 06, pp 178 - 187) to evaluate the performance of an IEEE 802.11e infrastructure network carrying packet telephone calls, streaming video sessions and TCP controlled file downloads, using Enhanced Distributed Channel Access (EDCA). We identify the time boundaries of activities on the channel (called channel slot boundaries) and derive a Markov Renewal Process of the contending nodes on these epochs. This is achieved by the use of attempt probabilities of the contending nodes as those obtained from the saturation fixed point analysis of (Ramaiyan et al. 2005. In Proceedings ACM Sigmetrics, `05. Journal version accepted for publication in IEEE TON). Regenerative analysis on this MRP yields the desired steady state performance measures. We then use the MRP model to develop an effective bandwidth approach for obtaining a bound on the size of the buffer required at the video queue of the AP, such that the streaming video packet loss probability is kept to less than 1%. The results obtained match well with simulations using the network simulator, ns-2. We find that, with the default IEEE 802.11e EDCA parameters for access categories AC 1, AC 2 and AC 3, the voice call capacity decreases if even one streaming video session and one TCP file download are initiated by some wireless station. Subsequently, reducing the voice calls increases the video downlink stream throughput by 0.38 Mbps and file download capacity by 0.14 Mbps, for every voice call (for the 11 Mbps PHY). We find that a buffer size of 75KB is sufficient to ensure that the video packet loss probability at the QAP is within 1%.

A non-orthogonal distributed space-time coded protocol - Part 1:Signal model and design criteria

In this two-part series of papers, a generalized non-orthogonal amplify and forward (GNAF) protocol which generalizes several known cooperative diversity protocols is proposed. Transmission in the GNAF protocol comprises of two phases - the broadcast phase and the cooperation phase. In the broadcast phase, the source broadcasts its information to the relays as well as the destination. In the cooperation phase, the source and the relays together transmit a space-time code in a distributed fashion. The GNAF protocol relaxes the constraints imposed by the protocol of Jing and Hassibi on the code structure. In Part-I of this paper, a code design criteria is obtained and it is shown that the GNAF protocol is delay efficient and coding gain efficient as well. Moreover GNAF protocol enables the use of sphere decoders at the destination with a non-exponential Maximum likelihood (ML) decoding complexity. In Part-II, several low decoding complexity code constructions are studied and a lower bound on the Diversity-Multiplexing Gain tradeoff of the GNAF protocol is obtained.

An analytical model for capacity evaluation of VoIP on HCCA and TCP file transfers over EDCA in an IEEE 802.11e WLAN

In the context of the IEEE 802.11e standard for WLANs, we provide an analytical model for obtaining the maximum number of VoIP calls that can be supported on HCCA, such that the delay QoS constraint of the accepted calls is met, when TCP downloads are coexistent on EDCA. In this scenario, we derive the TCP download throughput by using an analytical model for the case where only TCP sessions are present in the WLAN. We show that the analytical model for combined voice and TCP transfers provides accurate results in comparison with simulations (using ns-2).

An analytical model for the capacity estimation of combined VoIP and TCP file transfers over EDCA in an IEEE 802.11e WLAN

In this paper we develop and numerically explore the modeling heuristic of using saturation attempt probabilities as state dependent attempt probabilities in an IEEE 802.11e infrastructure network carrying packet telephone calls and TCP controlled file downloads, using Enhanced Distributed Channel Access (EDCA). We build upon the fixed point analysis and performance insights in [1]. When there are a certain number of nodes of each class contending for the channel (i.e., have nonempty queues), then their attempt probabilities are taken to be those obtained from saturation analysis for that number of nodes. Then we model the system queue dynamics at the network nodes. With the proposed heuristic, the system evolution at channel slot boundaries becomes a Markov renewal process, and regenerative analysis yields the desired performance measures.The results obtained from this approach match well with ns2 simulations. We find that, with the default IEEE 802.11e EDCA parameters for AC 1 and AC 3, the voice call capacity decreases if even one file download is initiated by some station. Subsequently, reducing the voice calls increases the file download capacity almost linearly (by 1/3 Mbps per voice call for the 11 Mbps PHY).

Performance analysis of single-symbol maximum likelihood decodable linear STBCs

Performance of space-time block codes can be improved using the coordinate interleaving of the input symbols from rotated M-ary phase shift keying (MPSK) and M-ary quadrature amplitude modulation (MQAM) constellations. This paper is on the performance analysis of coordinate-interleaved space-time codes, which are a subset of single-symbol maximum likelihood decodable linear space-time block codes, for wireless multiple antenna terminals. The analytical and simulation results show that full diversity is achievable. Using the equivalent single-input single-output model, simple expressions for the average bit error rates are derived over flat uncorrelated Rayleigh fading channels. Optimum rotation angles are found by finding the minimum of the average bit error rate curves.

An analytical model for an IEEE~802.11 WLAN using DCF with two types of VoIP calls

In this paper we develop and numerically explore the modeling heuristic of using saturation attempt probabilities as state dependent attempt probabilities in an IEEE 802.11e infrastructure network carrying packet telephone calls and TCP controlled file downloads, using enhanced distributed channel access (EDCA). We build upon the fixed point analysis and performance insights. When there are a certain number of nodes of each class contending for the channel (i.e., have nonempty queues), then their attempt probabilities are taken to be those obtained from saturation analysis for that number of nodes. Then we model the system queue dynamics at the network nodes. With the proposed heuristic, the system evolution at channel slot boundaries becomes a Markov renewal process, and regenerative analysis yields the desired performance measures. The results obtained from this approach match well with ns2 simulations. We find that, with the default IEEE 802.11e EDCA parameters for AC 1 and AC 3, the voice call capacity decreases if even one file download is initiated by some station. Subsequently, reducing the voice calls increases the file download capacity almost linearly (by 1/3 Mbps per voice call for the 11 Mbps PHY)

Error, Confidence, and Cost in Engineering Computations

The questions that one should answer in engineering computations - deterministic, probabilistic/randomized, as well as heuristic - are (i) how good the computed results/outputs are and (ii) how much the cost in terms of amount of computation and the amount of storage utilized in getting the outputs is. The absolutely errorfree quantities as well as the completely errorless computations done in a natural process can never be captured by any means that we have at our disposal. While the computations including the input real quantities in nature/natural processes are exact, all the computations that we do using a digital computer or are carried out in an embedded form are never exact. The input data for such computations are also never exact because any measuring instrument has inherent error of a fixed order associated with it and this error, as a matter of hypothesis and not as a matter of assumption, is not less than 0.005 per cent. Here by error we imply relative error bounds. The fact that exact error is never known under any circumstances and any context implies that the term error is nothing but error-bounds. Further, in engineering computations, it is the relative error or, equivalently, the relative error-bounds (and not the absolute error) which is supremely important in providing us the information regarding the quality of the results/outputs. Another important fact is that inconsistency and/or near-consistency in nature, i.e., in problems created from nature is completely nonexistent while in our modelling of the natural problems we may introduce inconsistency or near-inconsistency due to human error or due to inherent non-removable error associated with any measuring device or due to assumptions introduced to make the problem solvable or more easily solvable in practice. Thus if we discover any inconsistency or possibly any near-inconsistency in a mathematical model, it is certainly due to any or all of the three foregoing factors. We do, however, go ahead to solve such inconsistent/near-consistent problems and do get results that could be useful in real-world situations. The talk considers several deterministic, probabilistic, and heuristic algorithms in numerical optimisation, other numerical and statistical computations, and in PAC (probably approximately correct) learning models. It highlights the quality of the results/outputs through specifying relative error-bounds along with the associated confidence level, and the cost, viz., amount of computations and that of storage through complexity. It points out the limitation in error-free computations (wherever possible, i.e., where the number of arithmetic operations is finite and is known a priori) as well as in the usage of interval arithmetic. Further, the interdependence among the error, the confidence, and the cost is discussed.

Maximum likelihood algorithms for joint estimation of synchronisation impairments and channel in multiple input multiple output-orthogonal frequency division multiplexing system

Maximum likelihood (ML) algorithms, for the joint estimation of synchronisation impairments and channel in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system, are investigated in this work. A system model that takes into account the effects of carrier frequency offset, sampling frequency offset, symbol timing error and channel impulse response is formulated. Cramer-Rao lower bounds for the estimation of continuous parameters are derived, which show the coupling effect among different impairments and the significance of the joint estimation. The authors propose an ML algorithm for the estimation of synchronisation impairments and channel together, using the grid search method. To reduce the complexity of the joint grid search in the ML algorithm, a modified ML (MML) algorithm with multiple one-dimensional searches is also proposed. Further, a stage-wise ML (SML) algorithm using existing algorithms, which estimate less number of parameters, is also proposed. Performance of the estimation algorithms is studied through numerical simulations and it is found that the proposed ML and MML algorithms exhibit better performance than SML algorithm.

Maximum likelihood analysis of multi-stress accelerated life test data of series systems with competing log-normal causes of failure

This article presents frequentist inference of accelerated life test data of series systems with independent log-normal component lifetimes. The means of the component log-lifetimes are assumed to depend on the stress variables through a linear stress translation function that can accommodate the standard stress translation functions in the literature. An expectation-maximization algorithm is developed to obtain the maximum likelihood estimates of model parameters. The maximum likelihood estimates are then further refined by bootstrap, which is also used to infer about the component and system reliability metrics at usage stresses. The developed methodology is illustrated by analyzing a real as well as a simulated dataset. A simulation study is also carried out to judge the effectiveness of the bootstrap. It is found that in this model, application of bootstrap results in significant improvement over the simple maximum likelihood estimates.

Voice source characterization using pitch synchronous discrete cosine transform for speaker identification

A characterization of the voice source (VS) signal by the pitch synchronous (PS) discrete cosine transform (DCT) is proposed. With the integrated linear prediction residual (ILPR) as the VS estimate, the PS DCT of the ILPR is evaluated as a feature vector for speaker identification (SID). On TIMIT and YOHO databases, using a Gaussian mixture model (GMM)-based classifier, it performs on par with existing VS-based features. On the NIST 2003 database, fusion with a GMM-based classifier using MFCC features improves the identification accuracy by 12% in absolute terms, proving that the proposed characterization has good promise as a feature for SID studies. (C) 2015 Acoustical Society of America