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

Audio Coding

Pruning of an Audio Enhancing Deep Generative Neural Network

Arijit Biswas

This is a presentation of the paper (http://www.aes.org/e-lib/browse.cfm?elib=20769), presented virtually at the 148th Audio Engineering Society Convention (https://www.eventscribe.com/2020/VirtualVienna/).

Paper Details

Authors:
Arijit Biswas
Simon Plain, Arijit Biswas
Submitted On:
5 June 2020 - 5:12am
Short Link:
Type:
Document Year:
Cite

Document Files

AESConv148_Pruning of an Audio Enhancing Deep Generative Neural Network.pdf

(22)

Keywords

Subscribe

Send Author a Private Message
[1] Simon Plain, Arijit Biswas, "Pruning of an Audio Enhancing Deep Generative Neural Network", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5454. Accessed: Jul. 09, 2020.
@article{5454-20,
url = {http://sigport.org/5454},
author = {Simon Plain; Arijit Biswas },
publisher = {IEEE SigPort},
title = {Pruning of an Audio Enhancing Deep Generative Neural Network},
year = {2020} }
TY - EJOUR
T1 - Pruning of an Audio Enhancing Deep Generative Neural Network
AU - Simon Plain; Arijit Biswas
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5454
ER -
Simon Plain, Arijit Biswas. (2020). Pruning of an Audio Enhancing Deep Generative Neural Network. IEEE SigPort. http://sigport.org/5454
Simon Plain, Arijit Biswas, 2020. Pruning of an Audio Enhancing Deep Generative Neural Network. Available at: http://sigport.org/5454.
Simon Plain, Arijit Biswas. (2020). "Pruning of an Audio Enhancing Deep Generative Neural Network." Web.
1. Simon Plain, Arijit Biswas. Pruning of an Audio Enhancing Deep Generative Neural Network [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5454

Source Coding of Audio Signals with a Generative Model

Roy Fejgin
Janusz Klejsa
Lars Villemoes
Cong Zhou

These are the slides from the video presentation at ICASSP 2020 of the paper "Source Coding of Audio Signals with a Generative Model".

Paper Details

Authors:
Roy Fejgin
Janusz Klejsa
Lars Villemoes
Cong Zhou
Roy Fejgin, Janusz Klejsa, Lars Villemoes, Cong Zhou
Submitted On:
27 May 2020 - 2:04pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:

Document Files

SourceCodingAudioSignalsGenerativeModel-ICASSP2020.pdf

(21)

Keywords

Subscribe

Send Author a Private Message
[1] Roy Fejgin, Janusz Klejsa, Lars Villemoes, Cong Zhou, "Source Coding of Audio Signals with a Generative Model", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5443. Accessed: Jul. 09, 2020.
@article{5443-20,
url = {http://sigport.org/5443},
author = {Roy Fejgin; Janusz Klejsa; Lars Villemoes; Cong Zhou },
publisher = {IEEE SigPort},
title = {Source Coding of Audio Signals with a Generative Model},
year = {2020} }
TY - EJOUR
T1 - Source Coding of Audio Signals with a Generative Model
AU - Roy Fejgin; Janusz Klejsa; Lars Villemoes; Cong Zhou
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5443
ER -
Roy Fejgin, Janusz Klejsa, Lars Villemoes, Cong Zhou. (2020). Source Coding of Audio Signals with a Generative Model. IEEE SigPort. http://sigport.org/5443
Roy Fejgin, Janusz Klejsa, Lars Villemoes, Cong Zhou, 2020. Source Coding of Audio Signals with a Generative Model. Available at: http://sigport.org/5443.
Roy Fejgin, Janusz Klejsa, Lars Villemoes, Cong Zhou. (2020). "Source Coding of Audio Signals with a Generative Model." Web.
1. Roy Fejgin, Janusz Klejsa, Lars Villemoes, Cong Zhou. Source Coding of Audio Signals with a Generative Model [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5443

Source Coding of Audio Signals with a Generative Model

Janusz Klejsa
Lars Villemoes

We consider source coding of audio signals with the help of a generative model. We use a construction where a waveform is first quantized, yielding a finite bitrate representation. The waveform is then reconstructed by random sampling from a model conditioned on the quantized waveform. The proposed coding scheme is theoretically analyzed. Using SampleRNN as the generative model, we demonstrate that the proposed coding structure provides performance competitive with state-of-the-art source coding tools for specific categories of audio signals.

Paper Details

Authors:
Janusz Klejsa
Lars Villemoes
Roy Fejgin, Janusz Klejsa, Lars Villemoes, Cong Zhou
Submitted On:
14 April 2020 - 5:16am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

SourceCodingOfAudioSignals_ICASSP2020_demo.zip

(42)

Keywords

Subscribe

Send Author a Private Message
[1] Roy Fejgin, Janusz Klejsa, Lars Villemoes, Cong Zhou, "Source Coding of Audio Signals with a Generative Model", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5094. Accessed: Jul. 09, 2020.
@article{5094-20,
url = {http://sigport.org/5094},
author = {Roy Fejgin; Janusz Klejsa; Lars Villemoes; Cong Zhou },
publisher = {IEEE SigPort},
title = {Source Coding of Audio Signals with a Generative Model},
year = {2020} }
TY - EJOUR
T1 - Source Coding of Audio Signals with a Generative Model
AU - Roy Fejgin; Janusz Klejsa; Lars Villemoes; Cong Zhou
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5094
ER -
Roy Fejgin, Janusz Klejsa, Lars Villemoes, Cong Zhou. (2020). Source Coding of Audio Signals with a Generative Model. IEEE SigPort. http://sigport.org/5094
Roy Fejgin, Janusz Klejsa, Lars Villemoes, Cong Zhou, 2020. Source Coding of Audio Signals with a Generative Model. Available at: http://sigport.org/5094.
Roy Fejgin, Janusz Klejsa, Lars Villemoes, Cong Zhou. (2020). "Source Coding of Audio Signals with a Generative Model." Web.
1. Roy Fejgin, Janusz Klejsa, Lars Villemoes, Cong Zhou. Source Coding of Audio Signals with a Generative Model [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5094

A high efficient cascade coder with predictor blending method for lossless audio compression

Cezary Wernik

In this paper, the improvement of the cascaded prediction method was presented. The prediction method with backward adaptation and extended Ordinary Least Square (OLS+) was presented. An own approach to implementation of the effective context-dependent constant component removal block was used. Also the improved adaptive arithmetic coder with short, medium and long-term adaptation was used and the experiment was carried out comparing the results with other known lossless audio coders against which our method obtained the best efficiency.

Paper Details

Authors:
Cezary Wernik
Grzegorz Ulacha, Cezary Wernik
Submitted On:
28 March 2020 - 4:45pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Session:
Document Year:
Cite

Document Files

Ulacha_Wernik_DCC_2020_POSTER.pdf

(33)

Keywords

Additional Categories

Subscribe

Send Author a Private Message
[1] Grzegorz Ulacha, Cezary Wernik, "A high efficient cascade coder with predictor blending method for lossless audio compression", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5045. Accessed: Jul. 09, 2020.
@article{5045-20,
url = {http://sigport.org/5045},
author = {Grzegorz Ulacha; Cezary Wernik },
publisher = {IEEE SigPort},
title = {A high efficient cascade coder with predictor blending method for lossless audio compression},
year = {2020} }
TY - EJOUR
T1 - A high efficient cascade coder with predictor blending method for lossless audio compression
AU - Grzegorz Ulacha; Cezary Wernik
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5045
ER -
Grzegorz Ulacha, Cezary Wernik. (2020). A high efficient cascade coder with predictor blending method for lossless audio compression. IEEE SigPort. http://sigport.org/5045
Grzegorz Ulacha, Cezary Wernik, 2020. A high efficient cascade coder with predictor blending method for lossless audio compression. Available at: http://sigport.org/5045.
Grzegorz Ulacha, Cezary Wernik. (2020). "A high efficient cascade coder with predictor blending method for lossless audio compression." Web.
1. Grzegorz Ulacha, Cezary Wernik. A high efficient cascade coder with predictor blending method for lossless audio compression [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5045

Learning about perception of temporal fine structure by building audio codecs

Lars Villemoes

This is a poster presented Thursday August 22, 2019 at the International Symposium on Auditory and Audiological Research (ISAAR). https://www.isaar.eu/index.php

SP.72 - Learning about perception of temporal fine structure by building audio codecs

https://whova.com/embedded/session/isaar_201908/701162/

Paper Details

Authors:
Lars Villemoes
Lars Villemoes, Arijit Biswas, Heidi-Maria Lehtonen, Heiko Purnhagen
Submitted On:
1 October 2019 - 4:43am
Short Link:
Type:
Document Year:
Cite

Document Files

ISAAR19poster.pdf

(81)

Keywords

Subscribe

Send Author a Private Message
[1] Lars Villemoes, Arijit Biswas, Heidi-Maria Lehtonen, Heiko Purnhagen , "Learning about perception of temporal fine structure by building audio codecs", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4850. Accessed: Jul. 09, 2020.
@article{4850-19,
url = {http://sigport.org/4850},
author = {Lars Villemoes; Arijit Biswas; Heidi-Maria Lehtonen; Heiko Purnhagen },
publisher = {IEEE SigPort},
title = {Learning about perception of temporal fine structure by building audio codecs},
year = {2019} }
TY - EJOUR
T1 - Learning about perception of temporal fine structure by building audio codecs
AU - Lars Villemoes; Arijit Biswas; Heidi-Maria Lehtonen; Heiko Purnhagen
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4850
ER -
Lars Villemoes, Arijit Biswas, Heidi-Maria Lehtonen, Heiko Purnhagen . (2019). Learning about perception of temporal fine structure by building audio codecs. IEEE SigPort. http://sigport.org/4850
Lars Villemoes, Arijit Biswas, Heidi-Maria Lehtonen, Heiko Purnhagen , 2019. Learning about perception of temporal fine structure by building audio codecs. Available at: http://sigport.org/4850.
Lars Villemoes, Arijit Biswas, Heidi-Maria Lehtonen, Heiko Purnhagen . (2019). "Learning about perception of temporal fine structure by building audio codecs." Web.
1. Lars Villemoes, Arijit Biswas, Heidi-Maria Lehtonen, Heiko Purnhagen . Learning about perception of temporal fine structure by building audio codecs [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4850

EVS AND OPUS AUDIO CODERS PERFORMANCE EVALUATION FOR ORIENTAL AND ORCHESTRAL MUSICAL INSTRUMENTS

yasser zenhom

In modern telecommunication systems the channel bandwidth and the quality of the reconstructed decoded audio signals are considered as major telecommunication resources. New speech or audio coders must be carefully designed and implemented to meet these requirements. EVS and OPUS audio coders are new coders which used to improve the quality of the reconstructed audio signal at different output bitrates. These coders can operate with different input signal type. The performance of these coders must be evaluated in terms of the quality of the reconstructed signals.

Paper Details

Authors:
yasser zenhom
Yasser A. Zenhom, Eman Mohammed, Micheal N. Mikhael, Hala A. Mansour
Submitted On:
19 September 2019 - 7:46pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

The performance criteria of the EVS and OPUS audio coders and describe the performance evaluation results for oriental and orche

(86)

Keywords

Subscribe

Send Author a Private Message
[1] Yasser A. Zenhom, Eman Mohammed, Micheal N. Mikhael, Hala A. Mansour, "EVS AND OPUS AUDIO CODERS PERFORMANCE EVALUATION FOR ORIENTAL AND ORCHESTRAL MUSICAL INSTRUMENTS", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4753. Accessed: Jul. 09, 2020.
@article{4753-19,
url = {http://sigport.org/4753},
author = {Yasser A. Zenhom; Eman Mohammed; Micheal N. Mikhael; Hala A. Mansour },
publisher = {IEEE SigPort},
title = {EVS AND OPUS AUDIO CODERS PERFORMANCE EVALUATION FOR ORIENTAL AND ORCHESTRAL MUSICAL INSTRUMENTS},
year = {2019} }
TY - EJOUR
T1 - EVS AND OPUS AUDIO CODERS PERFORMANCE EVALUATION FOR ORIENTAL AND ORCHESTRAL MUSICAL INSTRUMENTS
AU - Yasser A. Zenhom; Eman Mohammed; Micheal N. Mikhael; Hala A. Mansour
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4753
ER -
Yasser A. Zenhom, Eman Mohammed, Micheal N. Mikhael, Hala A. Mansour. (2019). EVS AND OPUS AUDIO CODERS PERFORMANCE EVALUATION FOR ORIENTAL AND ORCHESTRAL MUSICAL INSTRUMENTS. IEEE SigPort. http://sigport.org/4753
Yasser A. Zenhom, Eman Mohammed, Micheal N. Mikhael, Hala A. Mansour, 2019. EVS AND OPUS AUDIO CODERS PERFORMANCE EVALUATION FOR ORIENTAL AND ORCHESTRAL MUSICAL INSTRUMENTS. Available at: http://sigport.org/4753.
Yasser A. Zenhom, Eman Mohammed, Micheal N. Mikhael, Hala A. Mansour. (2019). "EVS AND OPUS AUDIO CODERS PERFORMANCE EVALUATION FOR ORIENTAL AND ORCHESTRAL MUSICAL INSTRUMENTS." Web.
1. Yasser A. Zenhom, Eman Mohammed, Micheal N. Mikhael, Hala A. Mansour. EVS AND OPUS AUDIO CODERS PERFORMANCE EVALUATION FOR ORIENTAL AND ORCHESTRAL MUSICAL INSTRUMENTS [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4753

AUDIO CODING BASED ON SPECTRAL RECOVERY BY CONVOLUTIONAL NEURAL NETWORK

SEONGHYEON SHIN

This study proposes a new method of audio coding based on spectral recovery, which can enhance the performance of transform audio coding. An encoder represents spectral information of an input in a time-frequency domain and transmits only a portion of it so that the remaining spectral information can be recovered based on the transmitted information. A decoder recovers the magnitudes of missing spectral information using a convolutional neural network. The signs of missing spectral information are either transmitted or randomly assigned, according to their importance.

Paper Details

Authors:
SEONGHYEON SHIN
Seong-Hyeon Shin, Seung Kwon Beack, Taejin Lee, Hochong Park
Submitted On:
10 May 2019 - 6:05am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

AUDIO_CODING_BASED_ON_SPECTRAL_RECOVERY_BY_CONVOLUTIONAL_NEURAL_NETWORK.pdf

(91)

Keywords

Subscribe

Send Author a Private Message
[1] Seong-Hyeon Shin, Seung Kwon Beack, Taejin Lee, Hochong Park, "AUDIO CODING BASED ON SPECTRAL RECOVERY BY CONVOLUTIONAL NEURAL NETWORK", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4295. Accessed: Jul. 09, 2020.
@article{4295-19,
url = {http://sigport.org/4295},
author = {Seong-Hyeon Shin; Seung Kwon Beack; Taejin Lee; Hochong Park },
publisher = {IEEE SigPort},
title = {AUDIO CODING BASED ON SPECTRAL RECOVERY BY CONVOLUTIONAL NEURAL NETWORK},
year = {2019} }
TY - EJOUR
T1 - AUDIO CODING BASED ON SPECTRAL RECOVERY BY CONVOLUTIONAL NEURAL NETWORK
AU - Seong-Hyeon Shin; Seung Kwon Beack; Taejin Lee; Hochong Park
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4295
ER -
Seong-Hyeon Shin, Seung Kwon Beack, Taejin Lee, Hochong Park. (2019). AUDIO CODING BASED ON SPECTRAL RECOVERY BY CONVOLUTIONAL NEURAL NETWORK. IEEE SigPort. http://sigport.org/4295
Seong-Hyeon Shin, Seung Kwon Beack, Taejin Lee, Hochong Park, 2019. AUDIO CODING BASED ON SPECTRAL RECOVERY BY CONVOLUTIONAL NEURAL NETWORK. Available at: http://sigport.org/4295.
Seong-Hyeon Shin, Seung Kwon Beack, Taejin Lee, Hochong Park. (2019). "AUDIO CODING BASED ON SPECTRAL RECOVERY BY CONVOLUTIONAL NEURAL NETWORK." Web.
1. Seong-Hyeon Shin, Seung Kwon Beack, Taejin Lee, Hochong Park. AUDIO CODING BASED ON SPECTRAL RECOVERY BY CONVOLUTIONAL NEURAL NETWORK [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4295

Speaker-dependent WaveNet-based delay-free ADPCM speech coding

Takenori Yoshimura

This paper proposes a WaveNet-based delay-free adaptive differential pulse code modulation (ADPCM) speech coding system. The WaveNet generative model, which is a stateof-the-art model for neural-network-based speech waveform synthesis, is used as the adaptive predictor in ADPCM. To further improve speech quality, mel-cepstrum-based noise shaping and postfiltering were integrated with the proposed ADPCM system.

Paper Details

Authors:
Takenori Yoshimura
Submitted On:
7 May 2019 - 10:45pm
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

poster.pdf

(98)

Keywords

Subscribe

Send Author a Private Message
[1] , "Speaker-dependent WaveNet-based delay-free ADPCM speech coding", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3996. Accessed: Jul. 09, 2020.
@article{3996-19,
url = {http://sigport.org/3996},
author = { },
publisher = {IEEE SigPort},
title = {Speaker-dependent WaveNet-based delay-free ADPCM speech coding},
year = {2019} }
TY - EJOUR
T1 - Speaker-dependent WaveNet-based delay-free ADPCM speech coding
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3996
ER -
. (2019). Speaker-dependent WaveNet-based delay-free ADPCM speech coding. IEEE SigPort. http://sigport.org/3996
, 2019. Speaker-dependent WaveNet-based delay-free ADPCM speech coding. Available at: http://sigport.org/3996.
. (2019). "Speaker-dependent WaveNet-based delay-free ADPCM speech coding." Web.
1. . Speaker-dependent WaveNet-based delay-free ADPCM speech coding [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3996

Immersive Audio Coding for Virtual Reality Using a Metadata-Assisted Extension of the 3GPP EVS Codec

David Mcgrath

Virtual Reality (VR) audio scenes may be composed of a very large number of audio elements, including dynamic audio objects, fixed audio channels and scene-based audio elements such as Higher Order Ambisonics (HOA).

Paper Details

Authors:
David Mcgrath
David McGrath, Stefan Bruhn, Heiko Purnhagen, Michael Eckert, Juan Torres, Stefanie Brown, Dan Darcy
Submitted On:
7 May 2019 - 3:10pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

VRStream.pdf

(114)

Keywords

Subscribe

Send Author a Private Message
[1] David McGrath, Stefan Bruhn, Heiko Purnhagen, Michael Eckert, Juan Torres, Stefanie Brown, Dan Darcy, "Immersive Audio Coding for Virtual Reality Using a Metadata-Assisted Extension of the 3GPP EVS Codec", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3950. Accessed: Jul. 09, 2020.
@article{3950-19,
url = {http://sigport.org/3950},
author = {David McGrath; Stefan Bruhn; Heiko Purnhagen; Michael Eckert; Juan Torres; Stefanie Brown; Dan Darcy },
publisher = {IEEE SigPort},
title = {Immersive Audio Coding for Virtual Reality Using a Metadata-Assisted Extension of the 3GPP EVS Codec},
year = {2019} }
TY - EJOUR
T1 - Immersive Audio Coding for Virtual Reality Using a Metadata-Assisted Extension of the 3GPP EVS Codec
AU - David McGrath; Stefan Bruhn; Heiko Purnhagen; Michael Eckert; Juan Torres; Stefanie Brown; Dan Darcy
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3950
ER -
David McGrath, Stefan Bruhn, Heiko Purnhagen, Michael Eckert, Juan Torres, Stefanie Brown, Dan Darcy. (2019). Immersive Audio Coding for Virtual Reality Using a Metadata-Assisted Extension of the 3GPP EVS Codec. IEEE SigPort. http://sigport.org/3950
David McGrath, Stefan Bruhn, Heiko Purnhagen, Michael Eckert, Juan Torres, Stefanie Brown, Dan Darcy, 2019. Immersive Audio Coding for Virtual Reality Using a Metadata-Assisted Extension of the 3GPP EVS Codec. Available at: http://sigport.org/3950.
David McGrath, Stefan Bruhn, Heiko Purnhagen, Michael Eckert, Juan Torres, Stefanie Brown, Dan Darcy. (2019). "Immersive Audio Coding for Virtual Reality Using a Metadata-Assisted Extension of the 3GPP EVS Codec." Web.
1. David McGrath, Stefan Bruhn, Heiko Purnhagen, Michael Eckert, Juan Torres, Stefanie Brown, Dan Darcy. Immersive Audio Coding for Virtual Reality Using a Metadata-Assisted Extension of the 3GPP EVS Codec [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3950

WAVENET BASED LOW RATE SPEECH CODING

Quan Wang

Traditional parametric coding of speech facilitates low rate but provides poor reconstruction quality because of the inadequacy of the model used. We describe how a WaveNet generative speech model can be used to generate high quality speech from the bit stream of a standard parametric coder operating at 2.4 kb/s. We compare this parametric coder with a waveform coder based on the same generative model and show that approximating the signal waveform incurs a large rate penalty.

Paper Details

Authors:
Quan Wang
W. Bastiaan Kleijn, Felicia S. C. Lim, Alejandro Luebs, Jan Skoglund, Florian Stimberg, Quan Wang, Thomas C. Walters
Submitted On:
4 May 2018 - 2:28pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

WaveNetCoding_b.pdf

(284)

Keywords

Subscribe

Send Author a Private Message
[1] W. Bastiaan Kleijn, Felicia S. C. Lim, Alejandro Luebs, Jan Skoglund, Florian Stimberg, Quan Wang, Thomas C. Walters, "WAVENET BASED LOW RATE SPEECH CODING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3201. Accessed: Jul. 09, 2020.
@article{3201-18,
url = {http://sigport.org/3201},
author = {W. Bastiaan Kleijn; Felicia S. C. Lim; Alejandro Luebs; Jan Skoglund; Florian Stimberg; Quan Wang; Thomas C. Walters },
publisher = {IEEE SigPort},
title = {WAVENET BASED LOW RATE SPEECH CODING},
year = {2018} }
TY - EJOUR
T1 - WAVENET BASED LOW RATE SPEECH CODING
AU - W. Bastiaan Kleijn; Felicia S. C. Lim; Alejandro Luebs; Jan Skoglund; Florian Stimberg; Quan Wang; Thomas C. Walters
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3201
ER -
W. Bastiaan Kleijn, Felicia S. C. Lim, Alejandro Luebs, Jan Skoglund, Florian Stimberg, Quan Wang, Thomas C. Walters. (2018). WAVENET BASED LOW RATE SPEECH CODING. IEEE SigPort. http://sigport.org/3201
W. Bastiaan Kleijn, Felicia S. C. Lim, Alejandro Luebs, Jan Skoglund, Florian Stimberg, Quan Wang, Thomas C. Walters, 2018. WAVENET BASED LOW RATE SPEECH CODING. Available at: http://sigport.org/3201.
W. Bastiaan Kleijn, Felicia S. C. Lim, Alejandro Luebs, Jan Skoglund, Florian Stimberg, Quan Wang, Thomas C. Walters. (2018). "WAVENET BASED LOW RATE SPEECH CODING." Web.
1. W. Bastiaan Kleijn, Felicia S. C. Lim, Alejandro Luebs, Jan Skoglund, Florian Stimberg, Quan Wang, Thomas C. Walters. WAVENET BASED LOW RATE SPEECH CODING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3201

Pages