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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

Peak Detection and Baseline Correction using a Convolution Neural Network

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Authors:
Mikkel N. Schmidt, Tommy S. Alstrøm, Marcus Svendstorp, Jan Larsen
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14 May 2019 - 7:46am
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MLSP-L1.1_Alstrom_Tommy.pdf

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[1] Mikkel N. Schmidt, Tommy S. Alstrøm, Marcus Svendstorp, Jan Larsen, "Peak Detection and Baseline Correction using a Convolution Neural Network", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4503. Accessed: Sep. 21, 2019.
@article{4503-19,
url = {http://sigport.org/4503},
author = {Mikkel N. Schmidt; Tommy S. Alstrøm; Marcus Svendstorp; Jan Larsen },
publisher = {IEEE SigPort},
title = {Peak Detection and Baseline Correction using a Convolution Neural Network},
year = {2019} }
TY - EJOUR
T1 - Peak Detection and Baseline Correction using a Convolution Neural Network
AU - Mikkel N. Schmidt; Tommy S. Alstrøm; Marcus Svendstorp; Jan Larsen
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4503
ER -
Mikkel N. Schmidt, Tommy S. Alstrøm, Marcus Svendstorp, Jan Larsen. (2019). Peak Detection and Baseline Correction using a Convolution Neural Network. IEEE SigPort. http://sigport.org/4503
Mikkel N. Schmidt, Tommy S. Alstrøm, Marcus Svendstorp, Jan Larsen, 2019. Peak Detection and Baseline Correction using a Convolution Neural Network. Available at: http://sigport.org/4503.
Mikkel N. Schmidt, Tommy S. Alstrøm, Marcus Svendstorp, Jan Larsen. (2019). "Peak Detection and Baseline Correction using a Convolution Neural Network." Web.
1. Mikkel N. Schmidt, Tommy S. Alstrøm, Marcus Svendstorp, Jan Larsen. Peak Detection and Baseline Correction using a Convolution Neural Network [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4503

PROMISING ACCURATE PREFIX BOOSTING FOR SEQUENCE-TO-SEQUENCE ASR

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14 May 2019 - 3:25am
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[1] , "PROMISING ACCURATE PREFIX BOOSTING FOR SEQUENCE-TO-SEQUENCE ASR", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4502. Accessed: Sep. 21, 2019.
@article{4502-19,
url = {http://sigport.org/4502},
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/4502
ER -
. (2019). PROMISING ACCURATE PREFIX BOOSTING FOR SEQUENCE-TO-SEQUENCE ASR. IEEE SigPort. http://sigport.org/4502
, 2019. PROMISING ACCURATE PREFIX BOOSTING FOR SEQUENCE-TO-SEQUENCE ASR. Available at: http://sigport.org/4502.
. (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/4502

BACKGROUND ADAPTATION FOR IMPROVED LISTENING EXPERIENCE IN BROADCASTING


The intelligibility of speech in noise can be improved by modifying the speech. But with object-based audio, there
is the possibility of altering the background sound while leaving the speech unaltered. This may prove a less intrusive approach, affording good speech intelligibility without overly compromising the perceived sound quality. In this

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Authors:
Yan Tang, Qingju Liu, Bruno Fazenda, Weuwu Wang
Submitted On:
14 May 2019 - 2:49am
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ICASSP_TJC.pdf

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[1] Yan Tang, Qingju Liu, Bruno Fazenda, Weuwu Wang, "BACKGROUND ADAPTATION FOR IMPROVED LISTENING EXPERIENCE IN BROADCASTING", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4501. Accessed: Sep. 21, 2019.
@article{4501-19,
url = {http://sigport.org/4501},
author = {Yan Tang; Qingju Liu; Bruno Fazenda; Weuwu Wang },
publisher = {IEEE SigPort},
title = {BACKGROUND ADAPTATION FOR IMPROVED LISTENING EXPERIENCE IN BROADCASTING},
year = {2019} }
TY - EJOUR
T1 - BACKGROUND ADAPTATION FOR IMPROVED LISTENING EXPERIENCE IN BROADCASTING
AU - Yan Tang; Qingju Liu; Bruno Fazenda; Weuwu Wang
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4501
ER -
Yan Tang, Qingju Liu, Bruno Fazenda, Weuwu Wang. (2019). BACKGROUND ADAPTATION FOR IMPROVED LISTENING EXPERIENCE IN BROADCASTING. IEEE SigPort. http://sigport.org/4501
Yan Tang, Qingju Liu, Bruno Fazenda, Weuwu Wang, 2019. BACKGROUND ADAPTATION FOR IMPROVED LISTENING EXPERIENCE IN BROADCASTING. Available at: http://sigport.org/4501.
Yan Tang, Qingju Liu, Bruno Fazenda, Weuwu Wang. (2019). "BACKGROUND ADAPTATION FOR IMPROVED LISTENING EXPERIENCE IN BROADCASTING." Web.
1. Yan Tang, Qingju Liu, Bruno Fazenda, Weuwu Wang. BACKGROUND ADAPTATION FOR IMPROVED LISTENING EXPERIENCE IN BROADCASTING [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4501

ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS


In this paper we compare the quality of synthesized views produced by four DIBR methods when fed by depth maps estimated by five state-of-the-art stereo matching algorithms. Also, we compute the correlation between four popular metrics for ranking stereo matching algorithms and two metrics commonly used to evaluate synthesized views (PSNR and SSIM) plus one specific for DIBR.

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Authors:
Adriano Quilião de Oliveira, Thiago Lopes Trugillo da Silveira, Marcelo Walter, Cláudio Rosito Jung
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13 May 2019 - 9:19pm
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ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS

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[1] Adriano Quilião de Oliveira, Thiago Lopes Trugillo da Silveira, Marcelo Walter, Cláudio Rosito Jung, "ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4499. Accessed: Sep. 21, 2019.
@article{4499-19,
url = {http://sigport.org/4499},
author = {Adriano Quilião de Oliveira; Thiago Lopes Trugillo da Silveira; Marcelo Walter; Cláudio Rosito Jung },
publisher = {IEEE SigPort},
title = {ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS},
year = {2019} }
TY - EJOUR
T1 - ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS
AU - Adriano Quilião de Oliveira; Thiago Lopes Trugillo da Silveira; Marcelo Walter; Cláudio Rosito Jung
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4499
ER -
Adriano Quilião de Oliveira, Thiago Lopes Trugillo da Silveira, Marcelo Walter, Cláudio Rosito Jung. (2019). ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS. IEEE SigPort. http://sigport.org/4499
Adriano Quilião de Oliveira, Thiago Lopes Trugillo da Silveira, Marcelo Walter, Cláudio Rosito Jung, 2019. ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS. Available at: http://sigport.org/4499.
Adriano Quilião de Oliveira, Thiago Lopes Trugillo da Silveira, Marcelo Walter, Cláudio Rosito Jung. (2019). "ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS." Web.
1. Adriano Quilião de Oliveira, Thiago Lopes Trugillo da Silveira, Marcelo Walter, Cláudio Rosito Jung. ON THE PERFORMANCE OF DIBR METHODS WHEN USING DEPTH MAPS FROM STATE-OF-THE-ART STEREO MATCHING ALGORITHMS [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4499

A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties


Stochastic mirror descent (SMD) algorithms have recently garnered a great deal of attention in optimization, signal processing, and machine learning. They are similar to stochastic gradient descent (SGD), in that they perform updates along the negative gradient of an instantaneous (or stochastically chosen) loss function. However, rather than update the parameter (or weight) vector directly, they update it in a "mirrored" domain whose transformation is given by the gradient of a strictly convex differentiable potential function.

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Authors:
Navid Azizan, Babak Hassibi
Submitted On:
13 May 2019 - 8:33pm
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ICASSP-SMD-Poster.pdf

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[1] Navid Azizan, Babak Hassibi, "A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4498. Accessed: Sep. 21, 2019.
@article{4498-19,
url = {http://sigport.org/4498},
author = {Navid Azizan; Babak Hassibi },
publisher = {IEEE SigPort},
title = {A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties},
year = {2019} }
TY - EJOUR
T1 - A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties
AU - Navid Azizan; Babak Hassibi
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4498
ER -
Navid Azizan, Babak Hassibi. (2019). A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties. IEEE SigPort. http://sigport.org/4498
Navid Azizan, Babak Hassibi, 2019. A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties. Available at: http://sigport.org/4498.
Navid Azizan, Babak Hassibi. (2019). "A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties." Web.
1. Navid Azizan, Babak Hassibi. A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4498

PROMISING ACCURATE PREFIX BOOSTING FOR SEQUENCE-TO-SEQUENCE ASR

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Authors:
Submitted On:
13 May 2019 - 7:22pm
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PAPB_icassp-expanded.pdf

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[1] , "PROMISING ACCURATE PREFIX BOOSTING FOR SEQUENCE-TO-SEQUENCE ASR", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4496. Accessed: Sep. 21, 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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Authors:
Youye Xie, Michael B. Wakin, Gongguo Tang
Submitted On:
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: Sep. 21, 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
Submitted On:
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: Sep. 21, 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: Sep. 21, 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
Submitted On:
13 May 2019 - 1:47pm
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19ICASSP_Poster.pdf

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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: Sep. 21, 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

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