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Analysis of multitarget detection for speaker and language recognition

January 1, 2004
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Conference Paper
Author:
Elliot Singer
…
Published in:
ODYSSEY 2004, 31 May-4 June 2004.
Topic:
speaker recognition
R&D area:
R&D group:

Summary

The general multitarget detection (or open-set identification) task is the intersection of the more common tasks of close-set identification and open-set verification/detection. In this task, a bank of parallel detectors process an input and must decide if the input is from one of the target classes and, if so, which one (or a small set containing the true one). In this paper, we analyze theoretically and empirically the behavior of a multitarget detector and relate the identification confusion error and the miss and false alarm detection errors in predicting performance. We show analytically that the performance of a multitarget detector can be predicted from single detector performance using speaker and language recognition data and experiments.
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Summary

The general multitarget detection (or open-set identification) task is the intersection of the more common tasks of close-set identification and open-set verification/detection. In this task, a bank of parallel detectors process an input and must decide if the input is from one of the target classes and, if so, which...

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Analysis of multitarget detection for speaker and language recognition

Automated lip-reading for improved speech intelligibility

January 1, 2004
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Conference Paper
Author:
Matthew R. McClain
…
Published in:
Proc. of the IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP, Vol. I, 17-21 May 2004, pp. I-701 - I-704.
Topic:
speech processing
R&D area:
R&D group:

Summary

Various psycho-acoustical experiments have concluded that visual features strongly affect the perception of speech. This contribution is most pronounced in noisy environments where the intelligibility of audio-only speech is quickly degraded. An exploration of the effectiveness for extracted visual features such as lip height and width for improving speech intelligibility in noisy environments is provided in this paper. The intelligibility content of these extracted visual features will be investigated through an intelligibility test on an animated rendition of the video generated from the extracted visual features, as well as on the original video. These experiments demonstrate that the extracted video features do contain important aspects of intelligibility that may be utilized in augmenting speech enhancement and coding applications. Alternatively, these extracted visual features can be transmitted in a bandwidth effective way to augment speech coders.
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Summary

Various psycho-acoustical experiments have concluded that visual features strongly affect the perception of speech. This contribution is most pronounced in noisy environments where the intelligibility of audio-only speech is quickly degraded. An exploration of the effectiveness for extracted visual features such as lip height and width for improving speech intelligibility...

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Automated lip-reading for improved speech intelligibility

High performance computing productivity model synthesis

January 1, 2004
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Journal Article
Author:
Jeremy Kepner
Published in:
Int. J. High Perform. Comp. App., Vol. 12, No. 4, Winter 2004, pp. 505-516.
Topic:
high performance computing
R&D area:
R&D group:

Summary

The Defense Advanced Research Projects Agency (DARPA) High Productivity Computing System (HPCS) program is developing systems that deliver increased value to users at a rate commensurate with the rate of improvement in the underlying technologies. For example, if the relevant technology was silicon, the goal of such a system would be to double in productivity (or value) every 18 months, following Moore's law. The key questions are how we define and measure productivity, and what the underlying technologies that affect productivity are. The goal of this paper is to synthesize from several different productivity models a single model that captures the main features of all the models. In addition we will start the process of putting the model on an empirical foundation by incorporating selected results from the software engineering and high performance computing (HPC) communities. An asymptotic analysis of the model is conducted to check that it makes sense in certain special cases. The model is extrapolated to a HPC context and several examples are explored, including HPC centers, HPC users, and interactive grid computing. Finally, the model hints at a profoundly different way of viewing HPC systems, where the user must be included in the equation, and innovative hardware is a key aspect to lowering the very high costs of HPC software.
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Summary

The Defense Advanced Research Projects Agency (DARPA) High Productivity Computing System (HPCS) program is developing systems that deliver increased value to users at a rate commensurate with the rate of improvement in the underlying technologies. For example, if the relevant technology was silicon, the goal of such a system would...

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High performance computing productivity model synthesis

HPC productivity: an overarching view

January 1, 2004
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Journal Article
Author:
Jeremy Kepner
Published in:
Int. J. High Perform. Comp. App., Vol. 18, No. 4, Winter 2004, pp. 393-397.
Topic:
high performance computing
R&D area:
R&D group:

Summary

The Defense Advanced Research Projects Agency (DARPA) High Productivity Computing Systems (HPCS) program is focused on providing a new generation of economically viable high productivity computing systems for national security and for the industrial user community. The value of a high performance computing (HPC) system to a user includes many factors, such as execution time on a particular problem, software development time, direct hardware costs, and indirect administrative and maintenance costs. This special issue, which focuses on HPC productivity, brings together, for the first time, a series of novel papers written by several distinguished authors who share their views on this topic. The topic of productivity in HPC is very new and the authors have been encouraged to speculate. The goal of this first paper is to present an overarching context and framework for the other papers and to define some common ideas that have emerged in considering the problem of HPC productivity. In addition, this paper defines several characteristic HPC workflows that are useful for understanding how users exploit HPC systems, and discusses the role of activity and purpose benchmarks in establishing an empirical basis for HPC productivity.
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Summary

The Defense Advanced Research Projects Agency (DARPA) High Productivity Computing Systems (HPCS) program is focused on providing a new generation of economically viable high productivity computing systems for national security and for the industrial user community. The value of a high performance computing (HPC) system to a user includes many...

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HPC productivity: an overarching view

MatlabMPI

January 1, 2004
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Journal Article
Author:
Jeremy Kepner
…
Published in:
Journal of Parallel and Distributed Computing, Vol. 64, No. 8, pp. 997-1005.
Topic:
high performance computing
R&D area:
R&D group:

Summary

In many projects the true costs of high performance computing are currently dominated by software. Addressing these costs may require shifting to higher level languages such as Matlab. MatlabMPI is a Matlab implementation of the Message Passing Interface (MPI) standard and allows any Matlab program to exploit multiple processors. MatlabMPI currently implements the basic six functions that are the core of the MPI point-to-point communications standard. The key technical innovation of MatlabMPI is that it implements the widely used MPI “look and feel” on top of standard Matlab file I/O, resulting in an extremely compact (?350 lines of code) and “pure” implementation which runs anywhere Matlab runs, and on any heterogeneous combination of computers. The performance has been tested on both shared and distributed memory parallel computers (e.g. Sun, SGI, HP, IBM, Linux, MacOSX and Windows). MatlabMPI can match the bandwidth of C based MPI at large message sizes. A test image filtering application using MatlabMPI achieved a speedup of ?300 using 304 CPUs and ?15% of the theoretical peak (450 Gigaflops) on an IBM SP2 at the Maui High Performance Computing Center. In addition, this entire parallel benchmark application was implemented in 70 software-lines-of-code, illustrating the high productivity of this approach. MatlabMPI is available for download on the web.
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Summary

In many projects the true costs of high performance computing are currently dominated by software. Addressing these costs may require shifting to higher level languages such as Matlab. MatlabMPI is a Matlab implementation of the Message Passing Interface (MPI) standard and allows any Matlab program to exploit multiple processors. MatlabMPI...

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MatlabMPI

Beyond cepstra: exploiting high-level information in speaker recognition

December 11, 2003
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Conference Paper
Author:
Douglas A. Reynolds
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Published in:
Proc. Multimodal User Authentication Workshop, 11-12 December, 2003, pp. 223-9.
Topic:
speaker recognition
R&D area:
R&D group:

Summary

Traditionally speaker recognition techniques have focused on using short-term, low-level acoustic information such as cepstra features extracted over 20-30 ms windows of speech. But speech is a complex behavior conveying more information about the speaker than merely the sounds that are characteristic of his vocal apparatus. This higher-level information includes speaker-specific prosodics, pronunciations, word usage and conversational style. In this paper, we review some of the techniques to extract and apply these sources of high-level information with results from the NIST 2003 Extended Data Task.
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Summary

Traditionally speaker recognition techniques have focused on using short-term, low-level acoustic information such as cepstra features extracted over 20-30 ms windows of speech. But speech is a complex behavior conveying more information about the speaker than merely the sounds that are characteristic of his vocal apparatus. This higher-level information includes...

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Beyond cepstra: exploiting high-level information in speaker recognition

Exploiting nonacoustic sensors for speech enhancement

December 11, 2003
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Conference Paper
Author:
Thomas F. Quatieri
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Published in:
Proc. Workshop on Multimodal User Authentication, 11-12 December 2003, pp. 66-73.
Topic:
speaker recognition
R&D area:
R&D group:

Summary

Nonacoustic sensors such as the general electromagnetic motion sensor (GEMS), the physiological microphone (P-mic), and the electroglottograph (EGG) offer multimodal approaches to speech processing and speaker and speech recognition. These sensors provide measurements of functions of the glottal excitation and, more generally, of the vocal tract articulator movements that are relatively immune to acoustic disturbances and can supplement the acoustic speech waveform. This paper describes an approach to speech enhancement that exploits these nonacoustic sensors according to their capability in representing specific speech characteristics in different frequency bands. Frequency-domain sensor phase, as well as magnitude, is found to contribute to signal enhancement. Preliminary testing involves the time-synchronous multi-sensor DARPA Advanced Speech Encoding Pilot Speech Corpus collected in a variety of harsh acoustic noise environments. The enhancement approach is illustrated with examples that indicate its applicability as a pre-processor to low-rate vocoding and speaker authentication, and for enhanced listening from degraded speech.
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Summary

Nonacoustic sensors such as the general electromagnetic motion sensor (GEMS), the physiological microphone (P-mic), and the electroglottograph (EGG) offer multimodal approaches to speech processing and speaker and speech recognition. These sensors provide measurements of functions of the glottal excitation and, more generally, of the vocal tract articulator movements that are...

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Exploiting nonacoustic sensors for speech enhancement

Multimodal speaker authentication using nonacuostic sensors

December 11, 2003
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Conference Paper
Author:
William M. Campbell
…
Published in:
Proc. Workshop on Multimodal User Authentication, 11-12 December 2003, pp. 215-222.
Topic:
speech enhancement
R&D area:
R&D group:

Summary

Many nonacoustic sensors are now available to augment user authentication. Devices such as the GEMS (glottal electromagnetic micro-power sensor), the EGG (electroglottograph), and the P-mic (physiological mic) all have distinct methods of measuring physical processes associated with speech production. A potential exciting aspect of the application of these sensors is that they are less influenced by acoustic noise than a microphone. A drawback of having many sensors available is the need to develop features and classification technologies appropriate to each sensor. We therefore learn feature extraction based on data. State of the art classification with Gaussian Mixture Models and Support Vector Machines is then applied for multimodal authentication. We apply our techniques to two databases--the Lawrence Livermore GEMS corpus and the DARPA Advanced Speech Encoding Pilot corpus. We show the potential of nonacoustic sensors to increase authentication accuracy in realistic situations.
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Summary

Many nonacoustic sensors are now available to augment user authentication. Devices such as the GEMS (glottal electromagnetic micro-power sensor), the EGG (electroglottograph), and the P-mic (physiological mic) all have distinct methods of measuring physical processes associated with speech production. A potential exciting aspect of the application of these sensors is...

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Multimodal speaker authentication using nonacuostic sensors

Passive operating system identification from TCP/IP packet headers

November 19, 2003
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Conference Paper
Author:
Richard P. Lippmann
…
Published in:
ICDM Workshop on Data Mining for Computer Security, DMSEC, 19 November 2003.
Topic:
machine learning
R&D area:
R&D group:

Summary

Accurate operating system (OS) identification by passive network traffic analysis can continuously update less-frequent active network scans and help interpret alerts from intrusion detection systems. The most recent open-source passive OS identification tool (ettercap) rejects 70% of all packets and has a high 75-class error rate of 30% for non-rejected packets on unseen test data. New classifiers were developed using machine-learning approaches including cross-validation testing, grouping OS names into fewer classes, and evaluating alternate classifier types. Nearest neighbor and binary tree classifiers provide a low 9-class OS identification error rate of roughly 10% on unseen data without rejecting packets. This error rate drops to nearly zero when 10% of the packets are rejected.
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Summary

Accurate operating system (OS) identification by passive network traffic analysis can continuously update less-frequent active network scans and help interpret alerts from intrusion detection systems. The most recent open-source passive OS identification tool (ettercap) rejects 70% of all packets and has a high 75-class error rate of 30% for non-rejected...

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Passive operating system identification from TCP/IP packet headers

Biometrically enhanced software-defined radios

November 17, 2003
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Conference Paper
Author:
Joseph P. Campbell Jr
…
Published in:
Software Defined Radio Tech. Conf., SDR, 17-19 November 2003.
Topic:
speaker recognition
R&D area:
R&D group:

Summary

Software-defined radios and cognitive radios offer tremendous promise, while having great need for user authentication. Authenticating users is essential to ensuring authorized access and actions in private and secure communications networks. User authentication for software-defined radios and cognitive radios is our focus here. We present various means of authenticating users to their radios and networks, authentication architectures, and the complementary combination of authenticators and architectures. Although devices can be strongly authenticated (e.g., cryptographically), reliably authenticating users is a challenge. To meet this challenge, we capitalize on new forms of user authentication combined with new authentication architectures to support features such as continuous user authentication and varying levels of trust-based authentication. We generalize biometrics to include recognizing user behaviors and use them in concert with knowledge- and token-based authenticators. An integrated approach to user authentication and user authentication architectures is presented here to enhance trusted radio communications networks.
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Summary

Software-defined radios and cognitive radios offer tremendous promise, while having great need for user authentication. Authenticating users is essential to ensuring authorized access and actions in private and secure communications networks. User authentication for software-defined radios and cognitive radios is our focus here. We present various means of authenticating users...

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Biometrically enhanced software-defined radios
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