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Audio and Acoustic Signal Processing

SPARCOM

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Authors:
Oren Solomon, Maor Mutzafi, Yonina C. Eldar and Mordechai Segev
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11 March 2017 - 8:47pm
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ICASSP2017_SPARCOM_V2.pptx

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[1] Oren Solomon, Maor Mutzafi, Yonina C. Eldar and Mordechai Segev, "SPARCOM", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1672. Accessed: May. 30, 2017.
@article{1672-17,
url = {http://sigport.org/1672},
author = {Oren Solomon; Maor Mutzafi; Yonina C. Eldar and Mordechai Segev },
publisher = {IEEE SigPort},
title = {SPARCOM},
year = {2017} }
TY - EJOUR
T1 - SPARCOM
AU - Oren Solomon; Maor Mutzafi; Yonina C. Eldar and Mordechai Segev
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1672
ER -
Oren Solomon, Maor Mutzafi, Yonina C. Eldar and Mordechai Segev. (2017). SPARCOM. IEEE SigPort. http://sigport.org/1672
Oren Solomon, Maor Mutzafi, Yonina C. Eldar and Mordechai Segev, 2017. SPARCOM. Available at: http://sigport.org/1672.
Oren Solomon, Maor Mutzafi, Yonina C. Eldar and Mordechai Segev. (2017). "SPARCOM." Web.
1. Oren Solomon, Maor Mutzafi, Yonina C. Eldar and Mordechai Segev. SPARCOM [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1672

VERY DEEP CONVOLUTIONAL NEURAL NETWORKS FOR RAW WAVEFORMS

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Authors:
Chia Dai, Wei Dai, Shuhui Qu, Juncheng Li, Samarjit Das
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6 March 2017 - 3:41pm
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deep network

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[1] Chia Dai, Wei Dai, Shuhui Qu, Juncheng Li, Samarjit Das, "VERY DEEP CONVOLUTIONAL NEURAL NETWORKS FOR RAW WAVEFORMS", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1662. Accessed: May. 30, 2017.
@article{1662-17,
url = {http://sigport.org/1662},
author = {Chia Dai; Wei Dai; Shuhui Qu; Juncheng Li; Samarjit Das },
publisher = {IEEE SigPort},
title = {VERY DEEP CONVOLUTIONAL NEURAL NETWORKS FOR RAW WAVEFORMS},
year = {2017} }
TY - EJOUR
T1 - VERY DEEP CONVOLUTIONAL NEURAL NETWORKS FOR RAW WAVEFORMS
AU - Chia Dai; Wei Dai; Shuhui Qu; Juncheng Li; Samarjit Das
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1662
ER -
Chia Dai, Wei Dai, Shuhui Qu, Juncheng Li, Samarjit Das. (2017). VERY DEEP CONVOLUTIONAL NEURAL NETWORKS FOR RAW WAVEFORMS. IEEE SigPort. http://sigport.org/1662
Chia Dai, Wei Dai, Shuhui Qu, Juncheng Li, Samarjit Das, 2017. VERY DEEP CONVOLUTIONAL NEURAL NETWORKS FOR RAW WAVEFORMS. Available at: http://sigport.org/1662.
Chia Dai, Wei Dai, Shuhui Qu, Juncheng Li, Samarjit Das. (2017). "VERY DEEP CONVOLUTIONAL NEURAL NETWORKS FOR RAW WAVEFORMS." Web.
1. Chia Dai, Wei Dai, Shuhui Qu, Juncheng Li, Samarjit Das. VERY DEEP CONVOLUTIONAL NEURAL NETWORKS FOR RAW WAVEFORMS [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1662

Particle Flow for Sequential Monte Carlo Implementation of Probability Hypothesis Density

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Authors:
Wenwu Wang, Yuxin Zhao
Submitted On:
6 March 2017 - 8:33am
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ICASSP -Yang.pdf

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[1] Wenwu Wang, Yuxin Zhao, "Particle Flow for Sequential Monte Carlo Implementation of Probability Hypothesis Density", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1648. Accessed: May. 30, 2017.
@article{1648-17,
url = {http://sigport.org/1648},
author = {Wenwu Wang; Yuxin Zhao },
publisher = {IEEE SigPort},
title = {Particle Flow for Sequential Monte Carlo Implementation of Probability Hypothesis Density},
year = {2017} }
TY - EJOUR
T1 - Particle Flow for Sequential Monte Carlo Implementation of Probability Hypothesis Density
AU - Wenwu Wang; Yuxin Zhao
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1648
ER -
Wenwu Wang, Yuxin Zhao. (2017). Particle Flow for Sequential Monte Carlo Implementation of Probability Hypothesis Density. IEEE SigPort. http://sigport.org/1648
Wenwu Wang, Yuxin Zhao, 2017. Particle Flow for Sequential Monte Carlo Implementation of Probability Hypothesis Density. Available at: http://sigport.org/1648.
Wenwu Wang, Yuxin Zhao. (2017). "Particle Flow for Sequential Monte Carlo Implementation of Probability Hypothesis Density." Web.
1. Wenwu Wang, Yuxin Zhao. Particle Flow for Sequential Monte Carlo Implementation of Probability Hypothesis Density [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1648

Towards Wireless Acoustic Sensor Networks for Location Estimation and Counting of Multiple Speakers in Real-life Conditions

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Authors:
Anastasios Alexandridis, Nikolaos Stefanakis, Athanasios Mouchtaris
Submitted On:
2 March 2017 - 3:35pm
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ICASSP2017_Presentation.pdf

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[1] Anastasios Alexandridis, Nikolaos Stefanakis, Athanasios Mouchtaris, "Towards Wireless Acoustic Sensor Networks for Location Estimation and Counting of Multiple Speakers in Real-life Conditions", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1594. Accessed: May. 30, 2017.
@article{1594-17,
url = {http://sigport.org/1594},
author = {Anastasios Alexandridis; Nikolaos Stefanakis; Athanasios Mouchtaris },
publisher = {IEEE SigPort},
title = {Towards Wireless Acoustic Sensor Networks for Location Estimation and Counting of Multiple Speakers in Real-life Conditions},
year = {2017} }
TY - EJOUR
T1 - Towards Wireless Acoustic Sensor Networks for Location Estimation and Counting of Multiple Speakers in Real-life Conditions
AU - Anastasios Alexandridis; Nikolaos Stefanakis; Athanasios Mouchtaris
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1594
ER -
Anastasios Alexandridis, Nikolaos Stefanakis, Athanasios Mouchtaris. (2017). Towards Wireless Acoustic Sensor Networks for Location Estimation and Counting of Multiple Speakers in Real-life Conditions. IEEE SigPort. http://sigport.org/1594
Anastasios Alexandridis, Nikolaos Stefanakis, Athanasios Mouchtaris, 2017. Towards Wireless Acoustic Sensor Networks for Location Estimation and Counting of Multiple Speakers in Real-life Conditions. Available at: http://sigport.org/1594.
Anastasios Alexandridis, Nikolaos Stefanakis, Athanasios Mouchtaris. (2017). "Towards Wireless Acoustic Sensor Networks for Location Estimation and Counting of Multiple Speakers in Real-life Conditions." Web.
1. Anastasios Alexandridis, Nikolaos Stefanakis, Athanasios Mouchtaris. Towards Wireless Acoustic Sensor Networks for Location Estimation and Counting of Multiple Speakers in Real-life Conditions [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1594

FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION

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Submitted On:
2 March 2017 - 2:18pm
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ICASSP2017_poster.pdf

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[1] , "FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1593. Accessed: May. 30, 2017.
@article{1593-17,
url = {http://sigport.org/1593},
author = { },
publisher = {IEEE SigPort},
title = {FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION},
year = {2017} }
TY - EJOUR
T1 - FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1593
ER -
. (2017). FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION. IEEE SigPort. http://sigport.org/1593
, 2017. FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION. Available at: http://sigport.org/1593.
. (2017). "FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION." Web.
1. . FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1593

FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION

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Authors:
Submitted On:
2 March 2017 - 2:18pm
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ICASSP2017_poster.pdf

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[1] , " FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1592. Accessed: May. 30, 2017.
@article{1592-17,
url = {http://sigport.org/1592},
author = { },
publisher = {IEEE SigPort},
title = { FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION},
year = {2017} }
TY - EJOUR
T1 - FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1592
ER -
. (2017). FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION. IEEE SigPort. http://sigport.org/1592
, 2017. FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION. Available at: http://sigport.org/1592.
. (2017). " FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION." Web.
1. . FULLY COMPLEX DEEP NEURAL NETWORK FOR PHASE-INCORPORATING MONAURAL SOURCE SEPARATION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1592

: Faster-than-Nyquist Spatiotemporal Symbol-level Precoding in the Downlink of Multiuser MISO Channels

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Authors:
Maha ALODEH, Danilo SPANO, Symeon CHATZINOTAS, Bjorn OTTERSTEN
Submitted On:
1 March 2017 - 7:55am
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Icassp_poster.pdf

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[1] Maha ALODEH, Danilo SPANO, Symeon CHATZINOTAS, Bjorn OTTERSTEN, ": Faster-than-Nyquist Spatiotemporal Symbol-level Precoding in the Downlink of Multiuser MISO Channels", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1550. Accessed: May. 30, 2017.
@article{1550-17,
url = {http://sigport.org/1550},
author = {Maha ALODEH; Danilo SPANO; Symeon CHATZINOTAS; Bjorn OTTERSTEN },
publisher = {IEEE SigPort},
title = {: Faster-than-Nyquist Spatiotemporal Symbol-level Precoding in the Downlink of Multiuser MISO Channels},
year = {2017} }
TY - EJOUR
T1 - : Faster-than-Nyquist Spatiotemporal Symbol-level Precoding in the Downlink of Multiuser MISO Channels
AU - Maha ALODEH; Danilo SPANO; Symeon CHATZINOTAS; Bjorn OTTERSTEN
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1550
ER -
Maha ALODEH, Danilo SPANO, Symeon CHATZINOTAS, Bjorn OTTERSTEN. (2017). : Faster-than-Nyquist Spatiotemporal Symbol-level Precoding in the Downlink of Multiuser MISO Channels. IEEE SigPort. http://sigport.org/1550
Maha ALODEH, Danilo SPANO, Symeon CHATZINOTAS, Bjorn OTTERSTEN, 2017. : Faster-than-Nyquist Spatiotemporal Symbol-level Precoding in the Downlink of Multiuser MISO Channels. Available at: http://sigport.org/1550.
Maha ALODEH, Danilo SPANO, Symeon CHATZINOTAS, Bjorn OTTERSTEN. (2017). ": Faster-than-Nyquist Spatiotemporal Symbol-level Precoding in the Downlink of Multiuser MISO Channels." Web.
1. Maha ALODEH, Danilo SPANO, Symeon CHATZINOTAS, Bjorn OTTERSTEN. : Faster-than-Nyquist Spatiotemporal Symbol-level Precoding in the Downlink of Multiuser MISO Channels [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1550

Supervised group nonnegative matrix factorisation with similarity constraints and applications to speaker identification


This paper presents supervised feature learning approaches for speaker identification that rely on nonnegative matrix factorisation. Recent studies have shown that group nonnegative matrix factorisation and task-driven supervised dictionary learning can help performing effective feature learning for audio classification problems.

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Authors:
victor bisot, slim essid, gaël richard
Submitted On:
1 March 2017 - 4:34am
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Slide for the presentation

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[1] victor bisot, slim essid, gaël richard, "Supervised group nonnegative matrix factorisation with similarity constraints and applications to speaker identification", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1539. Accessed: May. 30, 2017.
@article{1539-17,
url = {http://sigport.org/1539},
author = {victor bisot; slim essid; gaël richard },
publisher = {IEEE SigPort},
title = {Supervised group nonnegative matrix factorisation with similarity constraints and applications to speaker identification},
year = {2017} }
TY - EJOUR
T1 - Supervised group nonnegative matrix factorisation with similarity constraints and applications to speaker identification
AU - victor bisot; slim essid; gaël richard
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1539
ER -
victor bisot, slim essid, gaël richard. (2017). Supervised group nonnegative matrix factorisation with similarity constraints and applications to speaker identification. IEEE SigPort. http://sigport.org/1539
victor bisot, slim essid, gaël richard, 2017. Supervised group nonnegative matrix factorisation with similarity constraints and applications to speaker identification. Available at: http://sigport.org/1539.
victor bisot, slim essid, gaël richard. (2017). "Supervised group nonnegative matrix factorisation with similarity constraints and applications to speaker identification." Web.
1. victor bisot, slim essid, gaël richard. Supervised group nonnegative matrix factorisation with similarity constraints and applications to speaker identification [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1539

CODING OF FINE GRANULAR AUDIO SIGNALS USING HIGH RESOLUTION ENVELOPE PROCESSING (HREP)


High Resolution Envelope Processing (HREP) is a new tool for improved perceptual coding of audio signals that predominantly consist of many dense transient events, such as applause, rain drop sounds, etc. These signals have traditionally been very difficult to code for perceptual audio codecs, particularly at low bit rates. Based on the gain control principle, HREP acts as a pre-/post-processor pair to perceptual audio codecs and preserves the temporal fine structure and subjective quality of applause-like signals.

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Authors:
Florin Ghido, Sascha Disch, Jürgen Herre, Franz Reutelhuber, Alexander Adami
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1 March 2017 - 4:15am
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ICASSP 2017 HREP Poster

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[1] Florin Ghido, Sascha Disch, Jürgen Herre, Franz Reutelhuber, Alexander Adami, "CODING OF FINE GRANULAR AUDIO SIGNALS USING HIGH RESOLUTION ENVELOPE PROCESSING (HREP)", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1538. Accessed: May. 30, 2017.
@article{1538-17,
url = {http://sigport.org/1538},
author = {Florin Ghido; Sascha Disch; Jürgen Herre; Franz Reutelhuber; Alexander Adami },
publisher = {IEEE SigPort},
title = {CODING OF FINE GRANULAR AUDIO SIGNALS USING HIGH RESOLUTION ENVELOPE PROCESSING (HREP)},
year = {2017} }
TY - EJOUR
T1 - CODING OF FINE GRANULAR AUDIO SIGNALS USING HIGH RESOLUTION ENVELOPE PROCESSING (HREP)
AU - Florin Ghido; Sascha Disch; Jürgen Herre; Franz Reutelhuber; Alexander Adami
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1538
ER -
Florin Ghido, Sascha Disch, Jürgen Herre, Franz Reutelhuber, Alexander Adami. (2017). CODING OF FINE GRANULAR AUDIO SIGNALS USING HIGH RESOLUTION ENVELOPE PROCESSING (HREP). IEEE SigPort. http://sigport.org/1538
Florin Ghido, Sascha Disch, Jürgen Herre, Franz Reutelhuber, Alexander Adami, 2017. CODING OF FINE GRANULAR AUDIO SIGNALS USING HIGH RESOLUTION ENVELOPE PROCESSING (HREP). Available at: http://sigport.org/1538.
Florin Ghido, Sascha Disch, Jürgen Herre, Franz Reutelhuber, Alexander Adami. (2017). "CODING OF FINE GRANULAR AUDIO SIGNALS USING HIGH RESOLUTION ENVELOPE PROCESSING (HREP)." Web.
1. Florin Ghido, Sascha Disch, Jürgen Herre, Franz Reutelhuber, Alexander Adami. CODING OF FINE GRANULAR AUDIO SIGNALS USING HIGH RESOLUTION ENVELOPE PROCESSING (HREP) [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1538

MULTILAYER SENSOR NETWORK FOR INFORMATION PRIVACY


A sensor network wishes to transmit information to a fusion center to allow it to detect a public hypothesis, but at the same time prevent it from inferring a private hypothesis. We propose a multilayer sensor network structure, where each sensor first applies a nonlinear fusion function on the information it receives from sensors in a previous layer, and then a linear weighting matrix to distort the information it sends to sensors in the next layer.

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Authors:
Xin He, Wee Peng Tay
Submitted On:
1 March 2017 - 1:57am
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ICASSP17_xin.pdf

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[1] Xin He, Wee Peng Tay, "MULTILAYER SENSOR NETWORK FOR INFORMATION PRIVACY", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1521. Accessed: May. 30, 2017.
@article{1521-17,
url = {http://sigport.org/1521},
author = {Xin He; Wee Peng Tay },
publisher = {IEEE SigPort},
title = {MULTILAYER SENSOR NETWORK FOR INFORMATION PRIVACY},
year = {2017} }
TY - EJOUR
T1 - MULTILAYER SENSOR NETWORK FOR INFORMATION PRIVACY
AU - Xin He; Wee Peng Tay
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1521
ER -
Xin He, Wee Peng Tay. (2017). MULTILAYER SENSOR NETWORK FOR INFORMATION PRIVACY. IEEE SigPort. http://sigport.org/1521
Xin He, Wee Peng Tay, 2017. MULTILAYER SENSOR NETWORK FOR INFORMATION PRIVACY. Available at: http://sigport.org/1521.
Xin He, Wee Peng Tay. (2017). "MULTILAYER SENSOR NETWORK FOR INFORMATION PRIVACY." Web.
1. Xin He, Wee Peng Tay. MULTILAYER SENSOR NETWORK FOR INFORMATION PRIVACY [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1521

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