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ICASSP 2019

ICASSP is the world’s largest and most comprehensive technical conference focused on signal processing and its applications. The 2019 conference will feature world-class presentations by internationally renowned speakers, cutting-edge session topics and provide a fantastic opportunity to network with like-minded professionals from around the world. Visit website

PROMISING ACCURATE PREFIX BOOSTING FOR SEQUENCE-TO-SEQUENCE ASR

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13 May 2019 - 7:22pm
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[1] , "PROMISING ACCURATE PREFIX BOOSTING FOR SEQUENCE-TO-SEQUENCE ASR", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4496. Accessed: May. 23, 2019.
@article{4496-19,
url = {http://sigport.org/4496},
author = { },
publisher = {IEEE SigPort},
title = {PROMISING ACCURATE PREFIX BOOSTING FOR SEQUENCE-TO-SEQUENCE ASR},
year = {2019} }
TY - EJOUR
T1 - PROMISING ACCURATE PREFIX BOOSTING FOR SEQUENCE-TO-SEQUENCE ASR
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4496
ER -
. (2019). PROMISING ACCURATE PREFIX BOOSTING FOR SEQUENCE-TO-SEQUENCE ASR. IEEE SigPort. http://sigport.org/4496
, 2019. PROMISING ACCURATE PREFIX BOOSTING FOR SEQUENCE-TO-SEQUENCE ASR. Available at: http://sigport.org/4496.
. (2019). "PROMISING ACCURATE PREFIX BOOSTING FOR SEQUENCE-TO-SEQUENCE ASR." Web.
1. . PROMISING ACCURATE PREFIX BOOSTING FOR SEQUENCE-TO-SEQUENCE ASR [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4496

Sparse Recovery and Non-stationary Blind Demodulation

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Youye Xie, Michael B. Wakin, Gongguo Tang
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13 May 2019 - 5:51pm
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[1] Youye Xie, Michael B. Wakin, Gongguo Tang, "Sparse Recovery and Non-stationary Blind Demodulation", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4494. Accessed: May. 23, 2019.
@article{4494-19,
url = {http://sigport.org/4494},
author = {Youye Xie; Michael B. Wakin; Gongguo Tang },
publisher = {IEEE SigPort},
title = {Sparse Recovery and Non-stationary Blind Demodulation},
year = {2019} }
TY - EJOUR
T1 - Sparse Recovery and Non-stationary Blind Demodulation
AU - Youye Xie; Michael B. Wakin; Gongguo Tang
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4494
ER -
Youye Xie, Michael B. Wakin, Gongguo Tang. (2019). Sparse Recovery and Non-stationary Blind Demodulation. IEEE SigPort. http://sigport.org/4494
Youye Xie, Michael B. Wakin, Gongguo Tang, 2019. Sparse Recovery and Non-stationary Blind Demodulation. Available at: http://sigport.org/4494.
Youye Xie, Michael B. Wakin, Gongguo Tang. (2019). "Sparse Recovery and Non-stationary Blind Demodulation." Web.
1. Youye Xie, Michael B. Wakin, Gongguo Tang. Sparse Recovery and Non-stationary Blind Demodulation [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4494

Learning from the best: A teacher-student multilingual framework for low-resource languages


The traditional method of pretraining neural acoustic models in low-resource languages consists of initializing the acoustic model parameters with a large, annotated multilingual corpus and can be a drain on time and resources. In an attempt to reuse TDNN-LSTMs already pre-trained using multilingual training, we have applied Teacher-Student (TS) learning as a method of pretraining to transfer knowledge from a multilingual TDNN-LSTM to a TDNN. The pretraining time is reduced by an order of magnitude with the use of language-specific data during the teacher-student training.

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Authors:
Deblin Bagchi and William Hartmann
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13 May 2019 - 5:43pm
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[1] Deblin Bagchi and William Hartmann, "Learning from the best: A teacher-student multilingual framework for low-resource languages", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4493. Accessed: May. 23, 2019.
@article{4493-19,
url = {http://sigport.org/4493},
author = {Deblin Bagchi and William Hartmann },
publisher = {IEEE SigPort},
title = {Learning from the best: A teacher-student multilingual framework for low-resource languages},
year = {2019} }
TY - EJOUR
T1 - Learning from the best: A teacher-student multilingual framework for low-resource languages
AU - Deblin Bagchi and William Hartmann
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4493
ER -
Deblin Bagchi and William Hartmann. (2019). Learning from the best: A teacher-student multilingual framework for low-resource languages. IEEE SigPort. http://sigport.org/4493
Deblin Bagchi and William Hartmann, 2019. Learning from the best: A teacher-student multilingual framework for low-resource languages. Available at: http://sigport.org/4493.
Deblin Bagchi and William Hartmann. (2019). "Learning from the best: A teacher-student multilingual framework for low-resource languages." Web.
1. Deblin Bagchi and William Hartmann. Learning from the best: A teacher-student multilingual framework for low-resource languages [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4493

COLLABORATION BETWEEN BORDEAUX-INP AND UTP, FROM RESEARCH TO EDUCATION, IN THE FIELD OF SIGNAL PROCESSING

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Authors:
Fernando Merchan, Héctor Poveda, Eric Grivel
Submitted On:
13 May 2019 - 4:57pm
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[1] Fernando Merchan, Héctor Poveda, Eric Grivel , "COLLABORATION BETWEEN BORDEAUX-INP AND UTP, FROM RESEARCH TO EDUCATION, IN THE FIELD OF SIGNAL PROCESSING", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4492. Accessed: May. 23, 2019.
@article{4492-19,
url = {http://sigport.org/4492},
author = {Fernando Merchan; Héctor Poveda; Eric Grivel },
publisher = {IEEE SigPort},
title = {COLLABORATION BETWEEN BORDEAUX-INP AND UTP, FROM RESEARCH TO EDUCATION, IN THE FIELD OF SIGNAL PROCESSING},
year = {2019} }
TY - EJOUR
T1 - COLLABORATION BETWEEN BORDEAUX-INP AND UTP, FROM RESEARCH TO EDUCATION, IN THE FIELD OF SIGNAL PROCESSING
AU - Fernando Merchan; Héctor Poveda; Eric Grivel
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4492
ER -
Fernando Merchan, Héctor Poveda, Eric Grivel . (2019). COLLABORATION BETWEEN BORDEAUX-INP AND UTP, FROM RESEARCH TO EDUCATION, IN THE FIELD OF SIGNAL PROCESSING. IEEE SigPort. http://sigport.org/4492
Fernando Merchan, Héctor Poveda, Eric Grivel , 2019. COLLABORATION BETWEEN BORDEAUX-INP AND UTP, FROM RESEARCH TO EDUCATION, IN THE FIELD OF SIGNAL PROCESSING. Available at: http://sigport.org/4492.
Fernando Merchan, Héctor Poveda, Eric Grivel . (2019). "COLLABORATION BETWEEN BORDEAUX-INP AND UTP, FROM RESEARCH TO EDUCATION, IN THE FIELD OF SIGNAL PROCESSING." Web.
1. Fernando Merchan, Héctor Poveda, Eric Grivel . COLLABORATION BETWEEN BORDEAUX-INP AND UTP, FROM RESEARCH TO EDUCATION, IN THE FIELD OF SIGNAL PROCESSING [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4492

LoRa digital receiver analysis and implementation

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Authors:
Reza Ghanaatian, Orion Afisiadis, Matthieu Cotting, Andreas Burg
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13 May 2019 - 1:47pm
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[1] Reza Ghanaatian, Orion Afisiadis, Matthieu Cotting, Andreas Burg, "LoRa digital receiver analysis and implementation", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4490. Accessed: May. 23, 2019.
@article{4490-19,
url = {http://sigport.org/4490},
author = {Reza Ghanaatian; Orion Afisiadis; Matthieu Cotting; Andreas Burg },
publisher = {IEEE SigPort},
title = {LoRa digital receiver analysis and implementation},
year = {2019} }
TY - EJOUR
T1 - LoRa digital receiver analysis and implementation
AU - Reza Ghanaatian; Orion Afisiadis; Matthieu Cotting; Andreas Burg
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4490
ER -
Reza Ghanaatian, Orion Afisiadis, Matthieu Cotting, Andreas Burg. (2019). LoRa digital receiver analysis and implementation. IEEE SigPort. http://sigport.org/4490
Reza Ghanaatian, Orion Afisiadis, Matthieu Cotting, Andreas Burg, 2019. LoRa digital receiver analysis and implementation. Available at: http://sigport.org/4490.
Reza Ghanaatian, Orion Afisiadis, Matthieu Cotting, Andreas Burg. (2019). "LoRa digital receiver analysis and implementation." Web.
1. Reza Ghanaatian, Orion Afisiadis, Matthieu Cotting, Andreas Burg. LoRa digital receiver analysis and implementation [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4490

Robust least squares estimation of graph signals


Recovering a graph signal from samples is a central problem in graph signal processing. Least mean squares (LMS) method for graph signal estimation is computationally efficient adaptive method. In this paper, we introduce a technique to robustify LMS with respect to mismatches in the presumed graph topology. It builds on the fact that graph LMS converges faster when the graph topology is specified correctly. We consider two measures of convergence speed, based on which we develop randomized greedy algorithms for robust interpolation of graph signals.

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Authors:
Jari Miettinen, Sergiy Vorobyov, Esa Ollila
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13 May 2019 - 12:55pm
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[1] Jari Miettinen, Sergiy Vorobyov, Esa Ollila, "Robust least squares estimation of graph signals", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4489. Accessed: May. 23, 2019.
@article{4489-19,
url = {http://sigport.org/4489},
author = {Jari Miettinen; Sergiy Vorobyov; Esa Ollila },
publisher = {IEEE SigPort},
title = {Robust least squares estimation of graph signals},
year = {2019} }
TY - EJOUR
T1 - Robust least squares estimation of graph signals
AU - Jari Miettinen; Sergiy Vorobyov; Esa Ollila
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4489
ER -
Jari Miettinen, Sergiy Vorobyov, Esa Ollila. (2019). Robust least squares estimation of graph signals. IEEE SigPort. http://sigport.org/4489
Jari Miettinen, Sergiy Vorobyov, Esa Ollila, 2019. Robust least squares estimation of graph signals. Available at: http://sigport.org/4489.
Jari Miettinen, Sergiy Vorobyov, Esa Ollila. (2019). "Robust least squares estimation of graph signals." Web.
1. Jari Miettinen, Sergiy Vorobyov, Esa Ollila. Robust least squares estimation of graph signals [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4489

In-Car Driver Authentication Using Wireless Sensing


Automobiles have become an essential part of everyday lives. In this work, we attempt to make them smarter by introducing the idea of in-car driver authentication using wireless sensing. Our aim is to develop a model which can recognize drivers automatically. Firstly, we address the problem of "changing in-car environments", where the existing wireless sensing based human identification system fails. To this end, we build the first in-car driver radio biometric dataset to understand the effect of changing environments on human radio biometrics.

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Authors:
Beibei Wang
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13 May 2019 - 11:17am
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[1] Beibei Wang, "In-Car Driver Authentication Using Wireless Sensing", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4487. Accessed: May. 23, 2019.
@article{4487-19,
url = {http://sigport.org/4487},
author = {Beibei Wang },
publisher = {IEEE SigPort},
title = {In-Car Driver Authentication Using Wireless Sensing},
year = {2019} }
TY - EJOUR
T1 - In-Car Driver Authentication Using Wireless Sensing
AU - Beibei Wang
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4487
ER -
Beibei Wang. (2019). In-Car Driver Authentication Using Wireless Sensing. IEEE SigPort. http://sigport.org/4487
Beibei Wang, 2019. In-Car Driver Authentication Using Wireless Sensing. Available at: http://sigport.org/4487.
Beibei Wang. (2019). "In-Car Driver Authentication Using Wireless Sensing." Web.
1. Beibei Wang. In-Car Driver Authentication Using Wireless Sensing [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4487

AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION


This paper proposes a group membership verification protocol preventing the curious but honest server from reconstructing the enrolled signatures and inferring the identity of querying clients. The protocol quantizes the signatures into discrete embeddings, making reconstruction difficult. It also aggregates multiple embeddings into representative values, impeding identification. Theoretical and experimental results show the trade-off between the security and error rates.

Paper Details

Authors:
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy
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13 May 2019 - 9:23am
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[1] Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy, "AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4486. Accessed: May. 23, 2019.
@article{4486-19,
url = {http://sigport.org/4486},
author = {Marzieh Gheisari; Teddy Furon; Laurent Amsaleg; Behrooz Razeghi; Slava Voloshynovskiy },
publisher = {IEEE SigPort},
title = {AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION},
year = {2019} }
TY - EJOUR
T1 - AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION
AU - Marzieh Gheisari; Teddy Furon; Laurent Amsaleg; Behrooz Razeghi; Slava Voloshynovskiy
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4486
ER -
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy. (2019). AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION. IEEE SigPort. http://sigport.org/4486
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy, 2019. AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION. Available at: http://sigport.org/4486.
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy. (2019). "AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION." Web.
1. Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy. AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4486

Estimation of Gaze Region using Two Dimensional Probabilistic Maps Constructed using Convolutional Neural Networks

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Authors:
Sumit Jha, Carlos Busso
Submitted On:
13 May 2019 - 9:22am
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[1] Sumit Jha, Carlos Busso, "Estimation of Gaze Region using Two Dimensional Probabilistic Maps Constructed using Convolutional Neural Networks", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4485. Accessed: May. 23, 2019.
@article{4485-19,
url = {http://sigport.org/4485},
author = {Sumit Jha; Carlos Busso },
publisher = {IEEE SigPort},
title = {Estimation of Gaze Region using Two Dimensional Probabilistic Maps Constructed using Convolutional Neural Networks},
year = {2019} }
TY - EJOUR
T1 - Estimation of Gaze Region using Two Dimensional Probabilistic Maps Constructed using Convolutional Neural Networks
AU - Sumit Jha; Carlos Busso
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4485
ER -
Sumit Jha, Carlos Busso. (2019). Estimation of Gaze Region using Two Dimensional Probabilistic Maps Constructed using Convolutional Neural Networks. IEEE SigPort. http://sigport.org/4485
Sumit Jha, Carlos Busso, 2019. Estimation of Gaze Region using Two Dimensional Probabilistic Maps Constructed using Convolutional Neural Networks. Available at: http://sigport.org/4485.
Sumit Jha, Carlos Busso. (2019). "Estimation of Gaze Region using Two Dimensional Probabilistic Maps Constructed using Convolutional Neural Networks." Web.
1. Sumit Jha, Carlos Busso. Estimation of Gaze Region using Two Dimensional Probabilistic Maps Constructed using Convolutional Neural Networks [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4485

AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION


This paper proposes a group membership verification protocol preventing the curious but honest server from reconstructing the enrolled signatures and inferring the identity of querying clients. The protocol quantizes the signatures into discrete embeddings, making reconstruction difficult. It also aggregates multiple embeddings into representative values, impeding identification. Theoretical and experimental results show the trade-off between the security and error rates.

Paper Details

Authors:
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy
Submitted On:
13 May 2019 - 9:23am
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Type:
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[1] Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy, "AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4484. Accessed: May. 23, 2019.
@article{4484-19,
url = {http://sigport.org/4484},
author = {Marzieh Gheisari; Teddy Furon; Laurent Amsaleg; Behrooz Razeghi; Slava Voloshynovskiy },
publisher = {IEEE SigPort},
title = {AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION},
year = {2019} }
TY - EJOUR
T1 - AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION
AU - Marzieh Gheisari; Teddy Furon; Laurent Amsaleg; Behrooz Razeghi; Slava Voloshynovskiy
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4484
ER -
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy. (2019). AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION. IEEE SigPort. http://sigport.org/4484
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy, 2019. AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION. Available at: http://sigport.org/4484.
Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy. (2019). "AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION." Web.
1. Marzieh Gheisari, Teddy Furon, Laurent Amsaleg, Behrooz Razeghi, Slava Voloshynovskiy. AGGREGATION AND EMBEDDING FOR GROUP MEMBERSHIP VERIFICATION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4484

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