Sorry, you need to enable JavaScript to visit this website.

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

DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM


This work considers a design of network in which multiple transmission points (TPs) cooperatively serve users by jointly precoding shared data. Considered problem formulation jointly designs the beamformers and performs TP-UE link selection, which aims in improving overall system rate. Proposed distributed Augmented ADMM algorithm features parallelization among TPs, which has practical importance for computational load distribution and reducing signaling overhead in backhaul.

Paper Details

Authors:
Submitted On:
3 May 2019 - 3:37pm
Short Link:
Type:
Event:
Document Year:
Cite

Document Files

Presentation poster for the paper.

(38)

Subscribe

[1] , "DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3905. Accessed: Aug. 24, 2019.
@article{3905-19,
url = {http://sigport.org/3905},
author = { },
publisher = {IEEE SigPort},
title = {DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM},
year = {2019} }
TY - EJOUR
T1 - DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3905
ER -
. (2019). DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM. IEEE SigPort. http://sigport.org/3905
, 2019. DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM. Available at: http://sigport.org/3905.
. (2019). "DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM." Web.
1. . DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3905

DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM


This work considers a design of network in which multiple transmission points (TPs) cooperatively serve users by jointly precoding shared data. Considered problem formulation jointly designs the beamformers and performs TP-UE link selection, which aims in improving overall system rate. Proposed distributed Augmented ADMM algorithm features parallelization among TPs, which has practical importance for computational load distribution and reducing signaling overhead in backhaul. This approach is different from others

Paper Details

Authors:
Submitted On:
3 May 2019 - 3:36pm
Short Link:
Type:
Event:
Document Year:
Cite

Document Files

Presentation poster for the paper.

(38)

Subscribe

[1] , "DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3904. Accessed: Aug. 24, 2019.
@article{3904-19,
url = {http://sigport.org/3904},
author = { },
publisher = {IEEE SigPort},
title = {DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM},
year = {2019} }
TY - EJOUR
T1 - DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3904
ER -
. (2019). DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM. IEEE SigPort. http://sigport.org/3904
, 2019. DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM. Available at: http://sigport.org/3904.
. (2019). "DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM." Web.
1. . DISTRIBUTED JOINT TRANSMITTER DESIGN AND SELECTION USING AUGMENTED ADMM [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3904

Nonlinear State Estimation using Particle Filters on the Stiefel Manifold


Many problems in statistical signal processing involve tracking the state of a dynamic system that evolves on a Stiefel manifold. To this aim, we introduce in this paper a novel particle filter algorithm that approximates the optimal importance function on the Stiefel manifold and is capable of handling nonlinear observation functions. To sample from the required importance function, we develop adaptations of previous MCMC algorithms.

Paper Details

Authors:
Claudio Bordin Jr., Marcelo G. S. Bruno
Submitted On:
8 May 2019 - 4:39pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

main.pdf

(28)

Subscribe

[1] Claudio Bordin Jr., Marcelo G. S. Bruno, "Nonlinear State Estimation using Particle Filters on the Stiefel Manifold", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3903. Accessed: Aug. 24, 2019.
@article{3903-19,
url = {http://sigport.org/3903},
author = {Claudio Bordin Jr.; Marcelo G. S. Bruno },
publisher = {IEEE SigPort},
title = {Nonlinear State Estimation using Particle Filters on the Stiefel Manifold},
year = {2019} }
TY - EJOUR
T1 - Nonlinear State Estimation using Particle Filters on the Stiefel Manifold
AU - Claudio Bordin Jr.; Marcelo G. S. Bruno
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3903
ER -
Claudio Bordin Jr., Marcelo G. S. Bruno. (2019). Nonlinear State Estimation using Particle Filters on the Stiefel Manifold. IEEE SigPort. http://sigport.org/3903
Claudio Bordin Jr., Marcelo G. S. Bruno, 2019. Nonlinear State Estimation using Particle Filters on the Stiefel Manifold. Available at: http://sigport.org/3903.
Claudio Bordin Jr., Marcelo G. S. Bruno. (2019). "Nonlinear State Estimation using Particle Filters on the Stiefel Manifold." Web.
1. Claudio Bordin Jr., Marcelo G. S. Bruno. Nonlinear State Estimation using Particle Filters on the Stiefel Manifold [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3903

SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION


Research about brain activities involving spoken word production is considerably underdeveloped because of the undiscovered characteristics of speech artifacts, which contaminate electroencephalogram (EEG) signals and prevent the inspection of the underlying cognitive processes. To fuel further EEG research with speech production, a method using three-mode tensor decomposition (time x space x frequency) is proposed to perform speech artifact removal. Tensor decomposition enables simultaneous inspection of multiple modes, which suits the multi-way nature of EEG data.

Paper Details

Authors:
Holy Lovenia, Hiroki Tanaka, Sakriani Sakti, Ayu Purwarianti, Satoshi Nakamura
Submitted On:
1 May 2019 - 4:29am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Holy Lovenia - ICASSP Poster (A0).pdf

(53)

Subscribe

[1] Holy Lovenia, Hiroki Tanaka, Sakriani Sakti, Ayu Purwarianti, Satoshi Nakamura, "SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3902. Accessed: Aug. 24, 2019.
@article{3902-19,
url = {http://sigport.org/3902},
author = {Holy Lovenia; Hiroki Tanaka; Sakriani Sakti; Ayu Purwarianti; Satoshi Nakamura },
publisher = {IEEE SigPort},
title = {SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION},
year = {2019} }
TY - EJOUR
T1 - SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION
AU - Holy Lovenia; Hiroki Tanaka; Sakriani Sakti; Ayu Purwarianti; Satoshi Nakamura
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3902
ER -
Holy Lovenia, Hiroki Tanaka, Sakriani Sakti, Ayu Purwarianti, Satoshi Nakamura. (2019). SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION. IEEE SigPort. http://sigport.org/3902
Holy Lovenia, Hiroki Tanaka, Sakriani Sakti, Ayu Purwarianti, Satoshi Nakamura, 2019. SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION. Available at: http://sigport.org/3902.
Holy Lovenia, Hiroki Tanaka, Sakriani Sakti, Ayu Purwarianti, Satoshi Nakamura. (2019). "SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION." Web.
1. Holy Lovenia, Hiroki Tanaka, Sakriani Sakti, Ayu Purwarianti, Satoshi Nakamura. SPEECH ARTIFACT REMOVAL FROM EEG RECORDINGS OF SPOKEN WORD PRODUCTION WITH TENSOR DECOMPOSITION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3902

[Poster] Localized Random Sampling for Robust Compressive Beam Alignment


Compressed sensing (CS)-based beam alignment is a promising solution for rapid link configuration in millimeter wave (mmWave)

Paper Details

Authors:
Nitin Jonathan Myers, Robert W. Heath Jr.
Submitted On:
30 April 2019 - 11:30pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

nitin_ICASSP_poster_v2.pdf

(50)

Subscribe

[1] Nitin Jonathan Myers, Robert W. Heath Jr., "[Poster] Localized Random Sampling for Robust Compressive Beam Alignment", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3900. Accessed: Aug. 24, 2019.
@article{3900-19,
url = {http://sigport.org/3900},
author = {Nitin Jonathan Myers; Robert W. Heath Jr. },
publisher = {IEEE SigPort},
title = {[Poster] Localized Random Sampling for Robust Compressive Beam Alignment},
year = {2019} }
TY - EJOUR
T1 - [Poster] Localized Random Sampling for Robust Compressive Beam Alignment
AU - Nitin Jonathan Myers; Robert W. Heath Jr.
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3900
ER -
Nitin Jonathan Myers, Robert W. Heath Jr.. (2019). [Poster] Localized Random Sampling for Robust Compressive Beam Alignment. IEEE SigPort. http://sigport.org/3900
Nitin Jonathan Myers, Robert W. Heath Jr., 2019. [Poster] Localized Random Sampling for Robust Compressive Beam Alignment. Available at: http://sigport.org/3900.
Nitin Jonathan Myers, Robert W. Heath Jr.. (2019). "[Poster] Localized Random Sampling for Robust Compressive Beam Alignment." Web.
1. Nitin Jonathan Myers, Robert W. Heath Jr.. [Poster] Localized Random Sampling for Robust Compressive Beam Alignment [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3900

MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION


Millimeter wave (mmWave) massive multiple input multiple output (MIMO) systems realizing directive beamforming require reliable estimation of the wireless propagation channel. However, mmWave channels are characterized by high variability that severely challenges their recovery over short training periods. Current channel estimation techniques exploit either the channel sparsity in the beamspace domain or its low-rank property in the antenna domain, nevertheless, they still require large numbers of training symbols for the satisfactory performance.

Paper Details

Authors:
E. Vlachos, G. Alexandropoulos, J. Thompson
Submitted On:
22 May 2019 - 11:17pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

IEEE Signal Processing Letters 2018

(46)

ICASSP19___Poster.pdf

(23)

Subscribe

[1] E. Vlachos, G. Alexandropoulos, J. Thompson, "MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3899. Accessed: Aug. 24, 2019.
@article{3899-19,
url = {http://sigport.org/3899},
author = {E. Vlachos; G. Alexandropoulos; J. Thompson },
publisher = {IEEE SigPort},
title = {MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION},
year = {2019} }
TY - EJOUR
T1 - MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION
AU - E. Vlachos; G. Alexandropoulos; J. Thompson
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3899
ER -
E. Vlachos, G. Alexandropoulos, J. Thompson. (2019). MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION. IEEE SigPort. http://sigport.org/3899
E. Vlachos, G. Alexandropoulos, J. Thompson, 2019. MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION. Available at: http://sigport.org/3899.
E. Vlachos, G. Alexandropoulos, J. Thompson. (2019). "MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION." Web.
1. E. Vlachos, G. Alexandropoulos, J. Thompson. MASSIVE MIMO CHANNEL ESTIMATION FOR MILLIMETER WAVE SYSTEMS VIA MATRIX COMPLETION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3899

IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN


In recent years, the successful application of Deep Learning methods to classification problems has had a huge impact in many domains. In biomedical engineering, the problem of gesture recognition based on electromyography is often addressed as an image classification problem using Convolutional Neural Networks. In this paper, we approach

Paper Details

Authors:
Panagiotis Tsinganos, Bruno Cornelis, Jan Cornelis, Bart Jansen, Athanassios Skodras
Submitted On:
7 May 2019 - 12:59pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Poster_A0_web.pdf

(34)

Subscribe

[1] Panagiotis Tsinganos, Bruno Cornelis, Jan Cornelis, Bart Jansen, Athanassios Skodras, "IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3898. Accessed: Aug. 24, 2019.
@article{3898-19,
url = {http://sigport.org/3898},
author = {Panagiotis Tsinganos; Bruno Cornelis; Jan Cornelis; Bart Jansen; Athanassios Skodras },
publisher = {IEEE SigPort},
title = {IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN},
year = {2019} }
TY - EJOUR
T1 - IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN
AU - Panagiotis Tsinganos; Bruno Cornelis; Jan Cornelis; Bart Jansen; Athanassios Skodras
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3898
ER -
Panagiotis Tsinganos, Bruno Cornelis, Jan Cornelis, Bart Jansen, Athanassios Skodras. (2019). IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN. IEEE SigPort. http://sigport.org/3898
Panagiotis Tsinganos, Bruno Cornelis, Jan Cornelis, Bart Jansen, Athanassios Skodras, 2019. IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN. Available at: http://sigport.org/3898.
Panagiotis Tsinganos, Bruno Cornelis, Jan Cornelis, Bart Jansen, Athanassios Skodras. (2019). "IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN." Web.
1. Panagiotis Tsinganos, Bruno Cornelis, Jan Cornelis, Bart Jansen, Athanassios Skodras. IMPROVED GESTURE RECOGNITION BASED ON sEMG SIGNALS AND TCN [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3898

Fully Supervised Speaker Diarization


In this paper, we propose a fully supervised speaker diarization approach, named unbounded interleaved-state recurrent neural networks (UIS-RNN). Given extracted speaker-discriminative embeddings (a.k.a. d-vectors) from input utterances, each individual speaker is modeled by a parameter-sharing RNN, while the RNN states for different speakers interleave in the time domain. This RNN is naturally integrated with a distance-dependent Chinese restaurant process (ddCRP) to accommodate an unknown number of speakers.

Paper Details

Authors:
Aonan Zhang, Quan Wang, Zhenyao Zhu, John Paisley, Chong Wang
Submitted On:
24 April 2019 - 11:06am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

icassp2019_supervised_diarization_poster.pdf

(63)

Subscribe

[1] Aonan Zhang, Quan Wang, Zhenyao Zhu, John Paisley, Chong Wang, " Fully Supervised Speaker Diarization", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3897. Accessed: Aug. 24, 2019.
@article{3897-19,
url = {http://sigport.org/3897},
author = {Aonan Zhang; Quan Wang; Zhenyao Zhu; John Paisley; Chong Wang },
publisher = {IEEE SigPort},
title = { Fully Supervised Speaker Diarization},
year = {2019} }
TY - EJOUR
T1 - Fully Supervised Speaker Diarization
AU - Aonan Zhang; Quan Wang; Zhenyao Zhu; John Paisley; Chong Wang
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3897
ER -
Aonan Zhang, Quan Wang, Zhenyao Zhu, John Paisley, Chong Wang. (2019). Fully Supervised Speaker Diarization. IEEE SigPort. http://sigport.org/3897
Aonan Zhang, Quan Wang, Zhenyao Zhu, John Paisley, Chong Wang, 2019. Fully Supervised Speaker Diarization. Available at: http://sigport.org/3897.
Aonan Zhang, Quan Wang, Zhenyao Zhu, John Paisley, Chong Wang. (2019). " Fully Supervised Speaker Diarization." Web.
1. Aonan Zhang, Quan Wang, Zhenyao Zhu, John Paisley, Chong Wang. Fully Supervised Speaker Diarization [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3897

Tuplemax Loss for Language Identification


In many scenarios of a language identification task, the user will specify a small set of languages which he/she can speak instead of a large set of all possible languages. We want to model such prior knowledge into the way we train our neural networks, by replacing the commonly used softmax loss function with a novel loss function named tuplemax loss. As a matter of fact, a typical language identification system launched in North America has about 95% users who could speak no more than two languages.

Paper Details

Authors:
Li Wan, Prashant Sridhar, Yang Yu, Quan Wang, Ignacio Lopez Moreno
Submitted On:
24 April 2019 - 11:03am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

poster

(42)

Subscribe

[1] Li Wan, Prashant Sridhar, Yang Yu, Quan Wang, Ignacio Lopez Moreno, "Tuplemax Loss for Language Identification", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3896. Accessed: Aug. 24, 2019.
@article{3896-19,
url = {http://sigport.org/3896},
author = {Li Wan; Prashant Sridhar; Yang Yu; Quan Wang; Ignacio Lopez Moreno },
publisher = {IEEE SigPort},
title = {Tuplemax Loss for Language Identification},
year = {2019} }
TY - EJOUR
T1 - Tuplemax Loss for Language Identification
AU - Li Wan; Prashant Sridhar; Yang Yu; Quan Wang; Ignacio Lopez Moreno
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3896
ER -
Li Wan, Prashant Sridhar, Yang Yu, Quan Wang, Ignacio Lopez Moreno. (2019). Tuplemax Loss for Language Identification. IEEE SigPort. http://sigport.org/3896
Li Wan, Prashant Sridhar, Yang Yu, Quan Wang, Ignacio Lopez Moreno, 2019. Tuplemax Loss for Language Identification. Available at: http://sigport.org/3896.
Li Wan, Prashant Sridhar, Yang Yu, Quan Wang, Ignacio Lopez Moreno. (2019). "Tuplemax Loss for Language Identification." Web.
1. Li Wan, Prashant Sridhar, Yang Yu, Quan Wang, Ignacio Lopez Moreno. Tuplemax Loss for Language Identification [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3896

HIGH-QUALITY SPEECH CODING WITH SAMPLE RNN


We provide a speech coding scheme employing a generative model based on SampleRNN that, while operating at significantly lower bitrates, matches or surpasses the perceptual quality of state-of-the-art classic wide-band codecs. Moreover, it is demonstrated that the proposed scheme can provide a meaningful rate-distortion trade-off without retraining. We evaluate the proposed scheme in a series of listening tests and discuss limitations of the approach.

Paper Details

Authors:
Janusz Klejsa, Per Hedelin, Cong Zhou, Roy Fejgin, Lars Villemoes
Submitted On:
23 May 2019 - 7:33am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Audio demo

(64)

Poster

(42)

Subscribe

[1] Janusz Klejsa, Per Hedelin, Cong Zhou, Roy Fejgin, Lars Villemoes, "HIGH-QUALITY SPEECH CODING WITH SAMPLE RNN", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3895. Accessed: Aug. 24, 2019.
@article{3895-19,
url = {http://sigport.org/3895},
author = {Janusz Klejsa; Per Hedelin; Cong Zhou; Roy Fejgin; Lars Villemoes },
publisher = {IEEE SigPort},
title = {HIGH-QUALITY SPEECH CODING WITH SAMPLE RNN},
year = {2019} }
TY - EJOUR
T1 - HIGH-QUALITY SPEECH CODING WITH SAMPLE RNN
AU - Janusz Klejsa; Per Hedelin; Cong Zhou; Roy Fejgin; Lars Villemoes
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3895
ER -
Janusz Klejsa, Per Hedelin, Cong Zhou, Roy Fejgin, Lars Villemoes. (2019). HIGH-QUALITY SPEECH CODING WITH SAMPLE RNN. IEEE SigPort. http://sigport.org/3895
Janusz Klejsa, Per Hedelin, Cong Zhou, Roy Fejgin, Lars Villemoes, 2019. HIGH-QUALITY SPEECH CODING WITH SAMPLE RNN. Available at: http://sigport.org/3895.
Janusz Klejsa, Per Hedelin, Cong Zhou, Roy Fejgin, Lars Villemoes. (2019). "HIGH-QUALITY SPEECH CODING WITH SAMPLE RNN." Web.
1. Janusz Klejsa, Per Hedelin, Cong Zhou, Roy Fejgin, Lars Villemoes. HIGH-QUALITY SPEECH CODING WITH SAMPLE RNN [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3895

Pages