The Experts below are selected from a list of 144 Experts worldwide ranked by ideXlab platform
Teruko Mitamura - One of the best experts on this subject based on the ideXlab platform.
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A Real-Time Mt System For Translating Broadcast Captions
1997Co-Authors: Eric Nyberg, Teruko MitamuraAbstract:This presentation demonstrates a new multi-engine machine translation system, which combines knowledge-based and example-based machine translation strategies for realtime translation of business news captions from English to German. 1. Introduction Broadcast captioning is derived from a textual transcription of a television broadcast, and is typically prouduced in real-time by a human operator using a stenography machine. The ASCII transcription is then encoded and transmitted in the vertical Blanking Interval (VBI) portion of the video signal. Some broadcasts (such as entertainment shows in syndication), are captioned off-line, but many shows of interest (such as "headline news" programs) are always captioned in real-time, with only a few seconds delay between the audio signal and the transcribed captions. Real-time translation of broadcast captioning poses several challenges for machine translation. The vocabulary and grammar of the source text are uncontrolled. It is not feasible t..
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A Real-Time Mt System For Translating Broadcast Captions
1997Co-Authors: Eric Nyberg And, Eric Nyberg, Teruko MitamuraAbstract:This presentation demonstrates a new multi-engine machine translation system, which combines knowledge-based and example-based machine translation strategies for realtime translation of business news captions from English to German. 1. Introduction Broadcast captioning is derived from a textual t ranscription of a television broadcast, and is typically prouduced in real-time by a human operator using a stenography machine. The ASCII transcription is then encoded and transmitted in the vertical Blanking Interval (VBI) portion of the video signal. Some broadcasts (such as entertainment shows in syndication), are captioned o ff-line, bu t many shows of interest (such as "headline news" programs) are always captioned in real-time, with only a few seconds delay between the audio signal and the transcribed captions. Real-time translation o f broadcast captioning poses s everal challenges for machine translation. The vocabulary and grammar of the source text are uncontrolled. It i s not ..
Kevin C Weng - One of the best experts on this subject based on the ideXlab platform.
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depth and range dependent variation in the performance of aquatic telemetry systems understanding and predicting the susceptibility of acoustic tag receiver pairs to close proximity detection interference
PeerJ, 2018Co-Authors: Stephen R Scherrer, Brendan P Rideout, Giacomo Giorli, Eva-marie Nosal, Kevin C WengAbstract:Background Passive acoustic telemetry using coded transmitter tags and stationary receivers is a popular method for tracking movements of aquatic animals. Understanding the performance of these systems is important in array design and in analysis. Close proximity detection interference (CPDI) is a condition where receivers fail to reliably detect tag transmissions. CPDI generally occurs when the tag and receiver are near one another in acoustically reverberant settings. Here we confirm transmission multipaths reflected off the environment arriving at a receiver with sufficient delay relative to the direct signal cause CPDI. We propose a ray-propagation based model to estimate the arrival of energy via multipaths to predict CPDI occurrence, and we show how deeper deployments are particularly susceptible. Methods A series of experiments were designed to develop and validate our model. Deep (300 m) and shallow (25 m) ranging experiments were conducted using Vemco V13 acoustic tags and VR2-W receivers. Probabilistic modeling of hourly detections was used to estimate the average distance a tag could be detected. A mechanistic model for predicting the arrival time of multipaths was developed using parameters from these experiments to calculate the direct and multipath path lengths. This model was retroactively applied to the previous ranging experiments to validate CPDI observations. Two additional experiments were designed to validate predictions of CPDI with respect to combinations of deployment depth and distance. Playback of recorded tags in a tank environment was used to confirm multipaths arriving after the receiver's Blanking Interval cause CPDI effects. Results Analysis of empirical data estimated the average maximum detection radius (AMDR), the farthest distance at which 95% of tag transmissions went undetected by receivers, was between 840 and 846 m for the deep ranging experiment across all factor permutations. From these results, CPDI was estimated within a 276.5 m radius of the receiver. These empirical estimations were consistent with mechanistic model predictions. CPDI affected detection at distances closer than 259-326 m from receivers. AMDR determined from the shallow ranging experiment was between 278 and 290 m with CPDI neither predicted nor observed. Results of validation experiments were consistent with mechanistic model predictions. Finally, we were able to predict detection/nondetection with 95.7% accuracy using the mechanistic model's criterion when simulating transmissions with and without multipaths. Discussion Close proximity detection interference results from combinations of depth and distance that produce reflected signals arriving after a receiver's Blanking Interval has ended. Deployment scenarios resulting in CPDI can be predicted with the proposed mechanistic model. For deeper deployments, sea-surface reflections can produce CPDI conditions, resulting in transmission rejection, regardless of the reflective properties of the seafloor.
Qi Fan - One of the best experts on this subject based on the ideXlab platform.
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ICASSP - A robust sequential detection algorithm for cardiac arrhythmia classification
1995 International Conference on Acoustics Speech and Signal Processing, 1Co-Authors: P.m. Clarkson, Szi-wen Chen, Qi FanAbstract:We describe a modified sequential probability ratio test (SPRT) for the discrimination of ventricular fibrillation (VF) from ventricular tachycardia (VT) in measured surface electrocardiograms. The algorithm uses a novel regularity measure dubbed Blanking variability (BV) applied to threshold crossings from the measured ECG. Blanking variability corresponds to the normalized rate of change of cardiac rate as the Blanking Interval is varied. The algorithm has been trained and tested using separate subsets drawn from the MIT-BIH malignant arrhythmia database. BV values are modeled using a truncated Gaussian distribution, and parameter values are derived by averaging over the training component of the database. In testing, the algorithm achieved an overall classification accuracy of 95%.
Eric Nyberg - One of the best experts on this subject based on the ideXlab platform.
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A Real-Time Mt System For Translating Broadcast Captions
1997Co-Authors: Eric Nyberg, Teruko MitamuraAbstract:This presentation demonstrates a new multi-engine machine translation system, which combines knowledge-based and example-based machine translation strategies for realtime translation of business news captions from English to German. 1. Introduction Broadcast captioning is derived from a textual transcription of a television broadcast, and is typically prouduced in real-time by a human operator using a stenography machine. The ASCII transcription is then encoded and transmitted in the vertical Blanking Interval (VBI) portion of the video signal. Some broadcasts (such as entertainment shows in syndication), are captioned off-line, but many shows of interest (such as "headline news" programs) are always captioned in real-time, with only a few seconds delay between the audio signal and the transcribed captions. Real-time translation of broadcast captioning poses several challenges for machine translation. The vocabulary and grammar of the source text are uncontrolled. It is not feasible t..
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A Real-Time Mt System For Translating Broadcast Captions
1997Co-Authors: Eric Nyberg And, Eric Nyberg, Teruko MitamuraAbstract:This presentation demonstrates a new multi-engine machine translation system, which combines knowledge-based and example-based machine translation strategies for realtime translation of business news captions from English to German. 1. Introduction Broadcast captioning is derived from a textual t ranscription of a television broadcast, and is typically prouduced in real-time by a human operator using a stenography machine. The ASCII transcription is then encoded and transmitted in the vertical Blanking Interval (VBI) portion of the video signal. Some broadcasts (such as entertainment shows in syndication), are captioned o ff-line, bu t many shows of interest (such as "headline news" programs) are always captioned in real-time, with only a few seconds delay between the audio signal and the transcribed captions. Real-time translation o f broadcast captioning poses s everal challenges for machine translation. The vocabulary and grammar of the source text are uncontrolled. It i s not ..
Stephen R Scherrer - One of the best experts on this subject based on the ideXlab platform.
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depth and range dependent variation in the performance of aquatic telemetry systems understanding and predicting the susceptibility of acoustic tag receiver pairs to close proximity detection interference
PeerJ, 2018Co-Authors: Stephen R Scherrer, Brendan P Rideout, Giacomo Giorli, Eva-marie Nosal, Kevin C WengAbstract:Background Passive acoustic telemetry using coded transmitter tags and stationary receivers is a popular method for tracking movements of aquatic animals. Understanding the performance of these systems is important in array design and in analysis. Close proximity detection interference (CPDI) is a condition where receivers fail to reliably detect tag transmissions. CPDI generally occurs when the tag and receiver are near one another in acoustically reverberant settings. Here we confirm transmission multipaths reflected off the environment arriving at a receiver with sufficient delay relative to the direct signal cause CPDI. We propose a ray-propagation based model to estimate the arrival of energy via multipaths to predict CPDI occurrence, and we show how deeper deployments are particularly susceptible. Methods A series of experiments were designed to develop and validate our model. Deep (300 m) and shallow (25 m) ranging experiments were conducted using Vemco V13 acoustic tags and VR2-W receivers. Probabilistic modeling of hourly detections was used to estimate the average distance a tag could be detected. A mechanistic model for predicting the arrival time of multipaths was developed using parameters from these experiments to calculate the direct and multipath path lengths. This model was retroactively applied to the previous ranging experiments to validate CPDI observations. Two additional experiments were designed to validate predictions of CPDI with respect to combinations of deployment depth and distance. Playback of recorded tags in a tank environment was used to confirm multipaths arriving after the receiver's Blanking Interval cause CPDI effects. Results Analysis of empirical data estimated the average maximum detection radius (AMDR), the farthest distance at which 95% of tag transmissions went undetected by receivers, was between 840 and 846 m for the deep ranging experiment across all factor permutations. From these results, CPDI was estimated within a 276.5 m radius of the receiver. These empirical estimations were consistent with mechanistic model predictions. CPDI affected detection at distances closer than 259-326 m from receivers. AMDR determined from the shallow ranging experiment was between 278 and 290 m with CPDI neither predicted nor observed. Results of validation experiments were consistent with mechanistic model predictions. Finally, we were able to predict detection/nondetection with 95.7% accuracy using the mechanistic model's criterion when simulating transmissions with and without multipaths. Discussion Close proximity detection interference results from combinations of depth and distance that produce reflected signals arriving after a receiver's Blanking Interval has ended. Deployment scenarios resulting in CPDI can be predicted with the proposed mechanistic model. For deeper deployments, sea-surface reflections can produce CPDI conditions, resulting in transmission rejection, regardless of the reflective properties of the seafloor.