Publications
Information Survivability for Mobile Wireless Systems
January 1, 2000
Journal Article
Published in:
Lincoln Laboratory Journal, Vol. 12, No. 1, pp. 65-80.
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Summary
Mobile wireless networks are more vulnerable to cyber attack and more difficult to defend than conventional wired networks. In discussing security and survivability issues in mobile wireless networks, we focus here on group communication, as applied to multimedia conferencing. The need to conserve resources in wireless networks encourages the use of multicast protocols for group communication, which introduces additional security concerns. We point out the need for rate-adaptation techniques to simultaneously support multiple receivers that each experience different network conditions. The security properties associated with a number of approaches to rate adaptation are compared. We also identify several security issues for reliable group communication, providing examples of denial-of-service attacks and describing appropriate security measures to guard against such attacks. We examine the costs of these security measures in terms of network efficiency and computational overhead. Finally, we introduce a survivability approach called dynamically deployed protocols, in which the effects of an information attack are mitigated by dynamically switching to a new protocol to evade the attack. We suggest that this dynamic protocol deployment can be achieved effectively by transmission of in-line mobile code.
Summary
Mobile wireless networks are more vulnerable to cyber attack and more difficult to defend than conventional wired networks. In discussing security and survivability issues in mobile wireless networks, we focus here on group communication, as applied to multimedia conferencing. The need to conserve resources in wireless networks encourages the use...
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Approaches to speaker detection and tracking in conversational speech
January 1, 2000
Journal Article
Published in:
Digit. Signal Process., Vol. 10, No. 1, January/April/July, 2000, pp. 93-112. (Fifth Annual NIST Speaker Recognition Workshop, 3-4 June 1999.)
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Two approaches to detecting and tracking speakers in multispeaker audio are described. Both approaches use an adapted Gaussian mixture model, universal background model (GMM-UBM) speaker detection system as the core speaker recognition engine. In one approach, the individual log-likelihood ratio scores, which are produced on a frame-by-frame basis by the GMM-UBM system, are used to first partition the speech file into speaker homogenous regions and then to create scores for these regions. We refer to this approach as internal segmentation. Another approach uses an external segmentation algorithm, based on blind clustering, to partition the speech file into speaker homogenous regions. The adapted GMM-UBM system then scores each of these regions as in the single-speaker recognition case. We show that the external segmentation system outperforms the internal segmentation system for both detection and tracking. In addition, we show how different components of the detection and tracking algorithms contribute to the overall system performance.
Summary
Two approaches to detecting and tracking speakers in multispeaker audio are described. Both approaches use an adapted Gaussian mixture model, universal background model (GMM-UBM) speaker detection system as the core speaker recognition engine. In one approach, the individual log-likelihood ratio scores, which are produced on a frame-by-frame basis by the...
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Speaker verification using adapted Gaussian mixture models
January 1, 2000
Journal Article
Published in:
Digit. Signal Process., Vol. 10, No. 1-3, January/April/July, 2000, pp. 19-41. (Fifth Annual NIST Speaker Recognition Workshop, 3-4 June 1999.)
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In this paper we describe the major elements of MIT Lincoln Laboratory's Gaussian mixture model (GMM)-based speaker verification system used successfully in several NIST Speaker Recognition Evaluations (SREs). The system is built around the likelihood ratio test for verification, using simple but effective GMMs for likelihood functions, a universal background model (UBM) for alternative speaker representation, and a form of Bayesian adaptation to derive speaker models from the UBM. The development and use of a handset detector and score normalization to greatly improve verification performance is also described and discussed. Finally, representative performance benchmarks and system behavior experiments on NIST SRE corpora are presented.
Summary
In this paper we describe the major elements of MIT Lincoln Laboratory's Gaussian mixture model (GMM)-based speaker verification system used successfully in several NIST Speaker Recognition Evaluations (SREs). The system is built around the likelihood ratio test for verification, using simple but effective GMMs for likelihood functions, a universal background...
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Cluster Computing for Embedded/Real-Time Systems
January 1, 2000
Book Chapter
Published in:
Cluster Computing White Paper
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Summary
Cluster computing is not a new area of computing. It is, however, evident that there is agrowing interest in its usage in all areas where applications have traditionally used parallelor distributed computing platforms. The mounting interest has been fuelled in part by theavailability of powerful microprocessors and high-speed networks as off-the-shelf commoditycomponents as well as in part by the rapidly maturing software components available tosupport high performance and high availability applications.This rising interest in clusters led to the formation of an IEEE Computer Society Task Forceon Cluster Computing (TFCC1) in early 1999. An objective of the TFCC was to act both as amagnet and a focal point for all cluster computing related activities. As such, an earlyactivity that was deemed necessary was to produce a White Paper on cluster computing andits related technologies.Generally a White Paper is looked upon as a statement of policy on a particular subject. Theaim of this White Paper is to provide a relatively unbiased report on the existing, new andemerging technologies as well as the surrounding infrastructure deemed important to thecluster computing community. This White Paper is essentially a snapshot of cluster-relatedtechnologies and applications in year 2000.This White Paper provides an authoritative review of all the hardware and softwaretechnologies that can be used to make up a cluster now or in the near future. Thesetechnologies range from the network level, through the operating system and middlewarelevels up to the application and tools level. The White Paper also tackles the increasinglyimportant areas of High Availability and Embedded/Real Time applications, which are bothconsidered crucial areas for future clusters.The White Paper has been broken down into twelve chapters, each of which has been puttogether by academics and industrial researchers who are both experts in their fields andwhere willing to volunteer their time and effort to put together this White Paper.On a personal note, I would like to thank all the contributing authors for finding the time toput the effort into their chapters and making the overall paper an excellent state-of-the-artreview of clusters. In addition, I would like to thank the reviewers for their timely comments.
Summary
Cluster computing is not a new area of computing. It is, however, evident that there is agrowing interest in its usage in all areas where applications have traditionally used parallelor distributed computing platforms. The mounting interest has been fuelled in part by theavailability of powerful microprocessors and high-speed networks as...
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The Vector, Signal, and Image Processing Library (VSIPL): an Open Standard for Astronomical Data Processing
December 1, 1999
Abstract
Published in:
Bulletin of the American Astronomical Society, Vol. 31, p.1497
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The Vector/Signal/Image Processing Library (VSIPL) is a DARPA initiated effort made up of industry, government and academic representatives who have defined an industry standard API for vector, signal, and image processing primitives for real-time signal processing on high performance systems. VSIPL supports a wide range of data types (int, float, complex, ...) and layouts (vectors, matrices and tensors) and is ideal for astronomical data processing. The VSIPL API is intended to serve as an open, vendor-neutral, industry standard interface. The object-based VSIPL API abstracts the memory architecture of the underlying machine by using the concept of memory blocks and views. Early experiments with VSIPL code conversions have been carried out by the High Performance Computing Program team at the UCSD. Commercially, several major vendors of signal processors are actively developing implementations. VSIPL has also been explicitly required as part of a recent Rome Labs teraflop procurement. This poster presents the VSIPL API, its functionality and the status of various implementations.
Summary
The Vector/Signal/Image Processing Library (VSIPL) is a DARPA initiated effort made up of industry, government and academic representatives who have defined an industry standard API for vector, signal, and image processing primitives for real-time signal processing on high performance systems. VSIPL supports a wide range of data types (int, float...
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Estimation of modulation based on FM-to-AM transduction: two-sinusoid case
November 1, 1999
Journal Article
Published in:
IEEE Trans. Signal Process., Vol. 47, No. 11, November 1999, pp. 3084-3097.
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A method is described for estimating the amplitude modulation (AM) and the frequency modulation (FM) of the components of a signal that consists of two AM-FM sinusoids. The approach is based on the transduction of FM to AM that occurs whenever a signal of varying frequency passes through a filter with a nonflat frequency response. The objective is to separate the AM and FM of the sinusoids from the amplitude envelopes of the output of two transduction filters, where the AM and FM are nonlinearly combined in the amplitude envelopes. A current scheme is first refined for AM-FM estimation of a single AM-FM sinusoid by iteratively inverting the AM and FM estimates to reduce error introduced in transduction. The transduction filter pair is designed relying on both a time-and frequency-domain characterization of transduction error. The approach is then extended to the case of two AM-FM sinusoids by essentially reducing the problem to two single-component AM-FM estimation problems. By exploiting the beating in the amplitude envelope of each filter output due to the two-sinusoidal input, a closed-form solution is obtained. This solution is also improved upon by iterative refinement. The AM-FM estimation methods are evaluated through an error analysis and are illustrated for a wide range of AM-FM signals.
Summary
A method is described for estimating the amplitude modulation (AM) and the frequency modulation (FM) of the components of a signal that consists of two AM-FM sinusoids. The approach is based on the transduction of FM to AM that occurs whenever a signal of varying frequency passes through a filter...
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Shunting networks for multi-band AM-FM decomposition
October 17, 1999
Conference Paper
Published in:
Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 17-20 October 1999.
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We describe a transduction-based, neurodynamic approach to estimating the amplitude-modulated (AM) and frequency-modulated (FM) components of a signal. We show that the transduction approach can be realized as a bank of constant-Q bandpass filters followed by envelope detectors and shunting neural networks, and the resulting dynamical system is capable of robust AM-FM estimation. Our model is consistent with recent psychophysical experiments that indicate AM and FM components of acoustic signals may be transformed into a common neural code in the brain stem via FM-to-AM transduction. The shunting network for AM-FM decomposition is followed by a contrast enhancement shunting network that provides a mechanism for robustly selecting auditory filter channels as the FM of an input stimulus sweeps across the multiple filters. The AM-FM output of the shunting networks may provide a robust feature representation and is being considered for applications in signal recognition and multi-component decomposition problems.
Summary
We describe a transduction-based, neurodynamic approach to estimating the amplitude-modulated (AM) and frequency-modulated (FM) components of a signal. We show that the transduction approach can be realized as a bank of constant-Q bandpass filters followed by envelope detectors and shunting neural networks, and the resulting dynamical system is capable of...
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A study of computation speed-ups of the GMM-UBM speaker recognition system
September 5, 1999
Conference Paper
Published in:
6th European Conf. on Speech Communication and Technology, EUROSPEECH, 5-9 September 1999.
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The Gaussian Mixture Model Universal Background Model (GMM-UBM) speaker recognition system has demonstrated very high performance in several NIST evaluations. Such evaluations, however, are concerned only with classification accuracy. In many applications, system effectiveness must be evaluated in light of both accuracy and execution speed. We present here a number of techniques for decreasing computation. Using data from the Switchboard telephone speech corpus, we show that significant speed-ups can be obtained while sacrificing surprisingly little accuracy. We expect that these techniques, involving lowering model order as well as processing fewer speech frames, will apply equally well to other recognition systems.
Summary
The Gaussian Mixture Model Universal Background Model (GMM-UBM) speaker recognition system has demonstrated very high performance in several NIST evaluations. Such evaluations, however, are concerned only with classification accuracy. In many applications, system effectiveness must be evaluated in light of both accuracy and execution speed. We present here a number...
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Evaluation of confidence measures for language identification
September 5, 1999
Conference Paper
Published in:
6th European Conf. on Speech Communication and Technology, EUROSPEECH, 5-9 September 1999.
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In this paper we examine various ways to derive confidence measures for a language identification system, using phone recognition followed by language models, and describe the application of an evaluation metric for measuring the "goodness" of the different confidence measures. Experiments are conducted on the 1996 NIST Language Identification Evaluation corpus (derived from the Callfriend corpus of conversational telephone speech). The system is trained on the NIST 96 development data and evaluated on the NIST 96 evaluation data. Results indicate that we are able to predict the performance of a system and quantitatively evaluate how well the prediction holds on new data.
Summary
In this paper we examine various ways to derive confidence measures for a language identification system, using phone recognition followed by language models, and describe the application of an evaluation metric for measuring the "goodness" of the different confidence measures. Experiments are conducted on the 1996 NIST Language Identification Evaluation...
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Speaker and language recognition using speech codec parameters
September 5, 1999
Conference Paper
Published in:
EUROSPEECH 99, 5-10 September 1999.
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Summary
In this paper, we investigate the effect of speech coding on speaker and language recognition tasks. Three coders were selected to cover a wide range of quality and bit rates: GSM at 12.2 kb/s, G.729 at 8 kb/s, and G.723.1 at 5.3 kb/s. Our objective is to measure recognition performance from either the synthesized speech or directly from the coder parameters themselves. We show that using speech synthesized from the three codecs, GMM-based speaker verification and phone-based language recognition performance generally degrades with coder bit rate, i.e., from GSM to G.729 to G.723.1, relative to an uncoded baseline. In addition, speaker verification for all codecs shows a performance decrease as the degree of mismatch between training and testing conditions increases, while language recognition exhibited no decrease in performance. We also present initial results in determining the relative importance of codec system components in their direct use for recognition tasks. For the G.729 codec, it is shown that removal of the post- filter in the decoder helps speaker verification performance under the mismatched condition. On the other hand, with use of G.729 LSF-based mel-cepstra, performance decreases under all conditions, indicating the need for a residual contribution to the feature representation.
Summary
In this paper, we investigate the effect of speech coding on speaker and language recognition tasks. Three coders were selected to cover a wide range of quality and bit rates: GSM at 12.2 kb/s, G.729 at 8 kb/s, and G.723.1 at 5.3 kb/s. Our objective is to measure recognition performance...
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