The Experts below are selected from a list of 72 Experts worldwide ranked by ideXlab platform
Prasanta Kumar Ghosh - One of the best experts on this subject based on the ideXlab platform.
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Speech Segmentation using Extrema-Based Signal Track Length Measure
2007 IEEE International Conference on Acoustics Speech and Signal Processing - ICASSP '07, 2007Co-Authors: Prasanta Kumar GhoshAbstract:We introduce a novel temporal feature of a Signal, namely extrema-based Signal Track length (ESTL) for the problem of speech segmentation. We show that ESTL measure is sensitive to both amplitude and frequency of the Signal. The short-time ESTL (ST_ESTL) shows a promising way to capture the significant segments of speech Signal, where the segments correspond to acoustic units of speech having distinct temporal waveforms. We compare ESTL based segmentation with ML and STM methods and find that it is as good as spectral feature based segmentation, but with lesser computational complexity.
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ICASSP (4) - Speech Segmentation using Extrema-Based Signal Track Length Measure
2007 IEEE International Conference on Acoustics Speech and Signal Processing - ICASSP '07, 2007Co-Authors: Prasanta Kumar GhoshAbstract:We introduce a novel temporal feature of a Signal, namely extrema-based Signal Track length (ESTL) for the problem of speech segmentation. We show that ESTL measure is sensitive to both amplitude and frequency of the Signal. The short-time ESTL (ST_ESTL) shows a promising way to capture the significant segments of speech Signal, where the segments correspond to acoustic units of speech having distinct temporal waveforms. We compare ESTL based segmentation with ML and STM methods and find that it is as good as spectral feature based segmentation, but with lesser computational complexity.
Robert J. Dempster - One of the best experts on this subject based on the ideXlab platform.
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False Track discrimination in a 3D Signal/Track processor
Proceedings of SPIE, 1996Co-Authors: Joseph B. Attili, Robert W. Fries, Cheuk L. Chan, Samuel S. Blackman, Paul Frank Singer, Robert J. DempsterAbstract:Long range detection and Tracking of moving targets against clutter requires advanced Signal and Track processing techniques in order to exploit the ultimate capabilities of modern electro-optical sensors. These include three- dimensional filtering and multiple hypothesis Tracking. Unfortunately, features present in real backgrounds can lead to false alarms which must be recognized in order to achieve a low false Track rate. This paper describes one approach which was successful at mitigating clutter-induced false Tracks while maintaining the low thresholds necessary for the detection of weak targets. This technique uses information derived in the Signal processor describing the local background as additional discriminants in the Track processor to identify false Tracks caused by clutter leakage. We present an overview of the 3D Signal Track/processor, the false Track mitigation methodology, and experimental results against real background data.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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False Track discrimination in a 3-D Signal/Track processor
1996Co-Authors: Joseph B. Attili, Robert W. Fries, Cheuk L. Chan, Paul Frank Singer, Sam Blackman, Robert J. DempsterAbstract:Long range detection and Tracking of moving targets against clutter requires advanced Signal and Track processing techniques in order to exploit the ultimate capabilities of modem electro-optical sensors. These include three-dimensional filtering and multiple hypothesis Tracking. Unfortunately, features present in real backgrounds can lead to false alarms which must be recognized in order to achieve a low false Track rate. This paper describes one approach which was successful at mitigating clutter-induced false Tracks while maintaining the low thresholds necessary for the detection of weak targets. This technique uses information derived in the Signal processor describing the local background as additional discriminants in the Track processor to identify false Tracks caused by clutter leakage. We present an overview of the 3-D Signal Track/processor, the false Track mitigation methodology, and experimental results against real background data.
Joseph B. Attili - One of the best experts on this subject based on the ideXlab platform.
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False Track discrimination in a 3D Signal/Track processor
Proceedings of SPIE, 1996Co-Authors: Joseph B. Attili, Robert W. Fries, Cheuk L. Chan, Samuel S. Blackman, Paul Frank Singer, Robert J. DempsterAbstract:Long range detection and Tracking of moving targets against clutter requires advanced Signal and Track processing techniques in order to exploit the ultimate capabilities of modern electro-optical sensors. These include three- dimensional filtering and multiple hypothesis Tracking. Unfortunately, features present in real backgrounds can lead to false alarms which must be recognized in order to achieve a low false Track rate. This paper describes one approach which was successful at mitigating clutter-induced false Tracks while maintaining the low thresholds necessary for the detection of weak targets. This technique uses information derived in the Signal processor describing the local background as additional discriminants in the Track processor to identify false Tracks caused by clutter leakage. We present an overview of the 3D Signal Track/processor, the false Track mitigation methodology, and experimental results against real background data.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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False Track discrimination in a 3-D Signal/Track processor
1996Co-Authors: Joseph B. Attili, Robert W. Fries, Cheuk L. Chan, Paul Frank Singer, Sam Blackman, Robert J. DempsterAbstract:Long range detection and Tracking of moving targets against clutter requires advanced Signal and Track processing techniques in order to exploit the ultimate capabilities of modem electro-optical sensors. These include three-dimensional filtering and multiple hypothesis Tracking. Unfortunately, features present in real backgrounds can lead to false alarms which must be recognized in order to achieve a low false Track rate. This paper describes one approach which was successful at mitigating clutter-induced false Tracks while maintaining the low thresholds necessary for the detection of weak targets. This technique uses information derived in the Signal processor describing the local background as additional discriminants in the Track processor to identify false Tracks caused by clutter leakage. We present an overview of the 3-D Signal Track/processor, the false Track mitigation methodology, and experimental results against real background data.
Paul Frank Singer - One of the best experts on this subject based on the ideXlab platform.
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False Track discrimination in a 3D Signal/Track processor
Proceedings of SPIE, 1996Co-Authors: Joseph B. Attili, Robert W. Fries, Cheuk L. Chan, Samuel S. Blackman, Paul Frank Singer, Robert J. DempsterAbstract:Long range detection and Tracking of moving targets against clutter requires advanced Signal and Track processing techniques in order to exploit the ultimate capabilities of modern electro-optical sensors. These include three- dimensional filtering and multiple hypothesis Tracking. Unfortunately, features present in real backgrounds can lead to false alarms which must be recognized in order to achieve a low false Track rate. This paper describes one approach which was successful at mitigating clutter-induced false Tracks while maintaining the low thresholds necessary for the detection of weak targets. This technique uses information derived in the Signal processor describing the local background as additional discriminants in the Track processor to identify false Tracks caused by clutter leakage. We present an overview of the 3D Signal Track/processor, the false Track mitigation methodology, and experimental results against real background data.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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False Track discrimination in a 3-D Signal/Track processor
1996Co-Authors: Joseph B. Attili, Robert W. Fries, Cheuk L. Chan, Paul Frank Singer, Sam Blackman, Robert J. DempsterAbstract:Long range detection and Tracking of moving targets against clutter requires advanced Signal and Track processing techniques in order to exploit the ultimate capabilities of modem electro-optical sensors. These include three-dimensional filtering and multiple hypothesis Tracking. Unfortunately, features present in real backgrounds can lead to false alarms which must be recognized in order to achieve a low false Track rate. This paper describes one approach which was successful at mitigating clutter-induced false Tracks while maintaining the low thresholds necessary for the detection of weak targets. This technique uses information derived in the Signal processor describing the local background as additional discriminants in the Track processor to identify false Tracks caused by clutter leakage. We present an overview of the 3-D Signal Track/processor, the false Track mitigation methodology, and experimental results against real background data.
Robert W. Fries - One of the best experts on this subject based on the ideXlab platform.
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False Track discrimination in a 3D Signal/Track processor
Proceedings of SPIE, 1996Co-Authors: Joseph B. Attili, Robert W. Fries, Cheuk L. Chan, Samuel S. Blackman, Paul Frank Singer, Robert J. DempsterAbstract:Long range detection and Tracking of moving targets against clutter requires advanced Signal and Track processing techniques in order to exploit the ultimate capabilities of modern electro-optical sensors. These include three- dimensional filtering and multiple hypothesis Tracking. Unfortunately, features present in real backgrounds can lead to false alarms which must be recognized in order to achieve a low false Track rate. This paper describes one approach which was successful at mitigating clutter-induced false Tracks while maintaining the low thresholds necessary for the detection of weak targets. This technique uses information derived in the Signal processor describing the local background as additional discriminants in the Track processor to identify false Tracks caused by clutter leakage. We present an overview of the 3D Signal Track/processor, the false Track mitigation methodology, and experimental results against real background data.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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False Track discrimination in a 3-D Signal/Track processor
1996Co-Authors: Joseph B. Attili, Robert W. Fries, Cheuk L. Chan, Paul Frank Singer, Sam Blackman, Robert J. DempsterAbstract:Long range detection and Tracking of moving targets against clutter requires advanced Signal and Track processing techniques in order to exploit the ultimate capabilities of modem electro-optical sensors. These include three-dimensional filtering and multiple hypothesis Tracking. Unfortunately, features present in real backgrounds can lead to false alarms which must be recognized in order to achieve a low false Track rate. This paper describes one approach which was successful at mitigating clutter-induced false Tracks while maintaining the low thresholds necessary for the detection of weak targets. This technique uses information derived in the Signal processor describing the local background as additional discriminants in the Track processor to identify false Tracks caused by clutter leakage. We present an overview of the 3-D Signal Track/processor, the false Track mitigation methodology, and experimental results against real background data.