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

Audio and Acoustic Signal Processing

END-TO-END JOINT LEARNING OF NATURAL LANGUAGE UNDERSTANDING AND DIALOGUE MANAGER

Paper Details

Authors:
Dilek Hakkani-Tür, Paul Crook, Xiujun Li, Jianfeng Gao, Li Deng
Submitted On:
12 April 2018 - 11:05pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

0308_icassp07.pptx

(44 downloads)

Subscribe

[1] Dilek Hakkani-Tür, Paul Crook, Xiujun Li, Jianfeng Gao, Li Deng, "END-TO-END JOINT LEARNING OF NATURAL LANGUAGE UNDERSTANDING AND DIALOGUE MANAGER", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2566. Accessed: Jul. 19, 2018.
@article{2566-18,
url = {http://sigport.org/2566},
author = {Dilek Hakkani-Tür; Paul Crook; Xiujun Li; Jianfeng Gao; Li Deng },
publisher = {IEEE SigPort},
title = {END-TO-END JOINT LEARNING OF NATURAL LANGUAGE UNDERSTANDING AND DIALOGUE MANAGER},
year = {2018} }
TY - EJOUR
T1 - END-TO-END JOINT LEARNING OF NATURAL LANGUAGE UNDERSTANDING AND DIALOGUE MANAGER
AU - Dilek Hakkani-Tür; Paul Crook; Xiujun Li; Jianfeng Gao; Li Deng
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2566
ER -
Dilek Hakkani-Tür, Paul Crook, Xiujun Li, Jianfeng Gao, Li Deng. (2018). END-TO-END JOINT LEARNING OF NATURAL LANGUAGE UNDERSTANDING AND DIALOGUE MANAGER. IEEE SigPort. http://sigport.org/2566
Dilek Hakkani-Tür, Paul Crook, Xiujun Li, Jianfeng Gao, Li Deng, 2018. END-TO-END JOINT LEARNING OF NATURAL LANGUAGE UNDERSTANDING AND DIALOGUE MANAGER. Available at: http://sigport.org/2566.
Dilek Hakkani-Tür, Paul Crook, Xiujun Li, Jianfeng Gao, Li Deng. (2018). "END-TO-END JOINT LEARNING OF NATURAL LANGUAGE UNDERSTANDING AND DIALOGUE MANAGER." Web.
1. Dilek Hakkani-Tür, Paul Crook, Xiujun Li, Jianfeng Gao, Li Deng. END-TO-END JOINT LEARNING OF NATURAL LANGUAGE UNDERSTANDING AND DIALOGUE MANAGER [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2566

Joint Modeling of Accents and Acoustics for Multi-Accent Speech Recognition

Paper Details

Authors:
Andrew Rosenberg, Samuel Thomas, Bhuvana Ramabhadran, Mark Hasegawa-Johnson
Submitted On:
12 April 2018 - 11:09pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

icassp18-poster (5).pdf

(31 downloads)

Subscribe

[1] Andrew Rosenberg, Samuel Thomas, Bhuvana Ramabhadran, Mark Hasegawa-Johnson, "Joint Modeling of Accents and Acoustics for Multi-Accent Speech Recognition", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2565. Accessed: Jul. 19, 2018.
@article{2565-18,
url = {http://sigport.org/2565},
author = {Andrew Rosenberg; Samuel Thomas; Bhuvana Ramabhadran; Mark Hasegawa-Johnson },
publisher = {IEEE SigPort},
title = {Joint Modeling of Accents and Acoustics for Multi-Accent Speech Recognition},
year = {2018} }
TY - EJOUR
T1 - Joint Modeling of Accents and Acoustics for Multi-Accent Speech Recognition
AU - Andrew Rosenberg; Samuel Thomas; Bhuvana Ramabhadran; Mark Hasegawa-Johnson
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2565
ER -
Andrew Rosenberg, Samuel Thomas, Bhuvana Ramabhadran, Mark Hasegawa-Johnson. (2018). Joint Modeling of Accents and Acoustics for Multi-Accent Speech Recognition. IEEE SigPort. http://sigport.org/2565
Andrew Rosenberg, Samuel Thomas, Bhuvana Ramabhadran, Mark Hasegawa-Johnson, 2018. Joint Modeling of Accents and Acoustics for Multi-Accent Speech Recognition. Available at: http://sigport.org/2565.
Andrew Rosenberg, Samuel Thomas, Bhuvana Ramabhadran, Mark Hasegawa-Johnson. (2018). "Joint Modeling of Accents and Acoustics for Multi-Accent Speech Recognition." Web.
1. Andrew Rosenberg, Samuel Thomas, Bhuvana Ramabhadran, Mark Hasegawa-Johnson. Joint Modeling of Accents and Acoustics for Multi-Accent Speech Recognition [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2565

INFLUENCE OF THE NUMBER OF LOUDSPEAKERS ON THE TIMBRE IN MIXED-ORDER AMBISONICS REPRODUTION


Ambisonics is a series of flexible spatial sound systems based on spatial harmonics decomposition and each order approximation of sound field. Accuracy and complexity of system increase with order. Considering that the horizontal localization resolution of human hearing is higher than vertical resolution, mixed-order Ambisonics (MOA) reconstructs horizontal sound field with higher order spatial harmonics, while reconstructs vertical sound field with lower order spatial harmonics, and thereby reaches a compromise between the perceptual performance and the complexity of system.

Paper Details

Authors:
Haiming Mai, Bosun Xie, Jianliang Jiang
Submitted On:
12 April 2018 - 10:29pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICASSP2018-Paper1435-Poster

(31 downloads)

Subscribe

[1] Haiming Mai, Bosun Xie, Jianliang Jiang, "INFLUENCE OF THE NUMBER OF LOUDSPEAKERS ON THE TIMBRE IN MIXED-ORDER AMBISONICS REPRODUTION", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2560. Accessed: Jul. 19, 2018.
@article{2560-18,
url = {http://sigport.org/2560},
author = {Haiming Mai; Bosun Xie; Jianliang Jiang },
publisher = {IEEE SigPort},
title = {INFLUENCE OF THE NUMBER OF LOUDSPEAKERS ON THE TIMBRE IN MIXED-ORDER AMBISONICS REPRODUTION},
year = {2018} }
TY - EJOUR
T1 - INFLUENCE OF THE NUMBER OF LOUDSPEAKERS ON THE TIMBRE IN MIXED-ORDER AMBISONICS REPRODUTION
AU - Haiming Mai; Bosun Xie; Jianliang Jiang
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2560
ER -
Haiming Mai, Bosun Xie, Jianliang Jiang. (2018). INFLUENCE OF THE NUMBER OF LOUDSPEAKERS ON THE TIMBRE IN MIXED-ORDER AMBISONICS REPRODUTION. IEEE SigPort. http://sigport.org/2560
Haiming Mai, Bosun Xie, Jianliang Jiang, 2018. INFLUENCE OF THE NUMBER OF LOUDSPEAKERS ON THE TIMBRE IN MIXED-ORDER AMBISONICS REPRODUTION. Available at: http://sigport.org/2560.
Haiming Mai, Bosun Xie, Jianliang Jiang. (2018). "INFLUENCE OF THE NUMBER OF LOUDSPEAKERS ON THE TIMBRE IN MIXED-ORDER AMBISONICS REPRODUTION." Web.
1. Haiming Mai, Bosun Xie, Jianliang Jiang. INFLUENCE OF THE NUMBER OF LOUDSPEAKERS ON THE TIMBRE IN MIXED-ORDER AMBISONICS REPRODUTION [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2560

AN EFFICIENT TARGET LOCALIZATION ESTIMATOR FROM BISTATIC RANGE AND TDOA MEASUREMENTS IN MULTISTATIC RADAR


This paper considers the target localization problem using the hybrid bistatic range and time difference of arrival (TDOA) measurements in multistatic radar. An algebraic closed-form solution to this nonlinear estimation problem is developed through two-stage processing, where the nuisance variables are introduced in the first stage and the localization error of first stage solution is estimated to improve the final target position estimate in the second stage.

Paper Details

Authors:
Submitted On:
12 April 2018 - 10:04pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICASSP2018-Zhaotao Qin-2653-Poster.pdf

(48 downloads)

Keywords

Additional Categories

Subscribe

[1] , "AN EFFICIENT TARGET LOCALIZATION ESTIMATOR FROM BISTATIC RANGE AND TDOA MEASUREMENTS IN MULTISTATIC RADAR", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2552. Accessed: Jul. 19, 2018.
@article{2552-18,
url = {http://sigport.org/2552},
author = { },
publisher = {IEEE SigPort},
title = {AN EFFICIENT TARGET LOCALIZATION ESTIMATOR FROM BISTATIC RANGE AND TDOA MEASUREMENTS IN MULTISTATIC RADAR},
year = {2018} }
TY - EJOUR
T1 - AN EFFICIENT TARGET LOCALIZATION ESTIMATOR FROM BISTATIC RANGE AND TDOA MEASUREMENTS IN MULTISTATIC RADAR
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2552
ER -
. (2018). AN EFFICIENT TARGET LOCALIZATION ESTIMATOR FROM BISTATIC RANGE AND TDOA MEASUREMENTS IN MULTISTATIC RADAR. IEEE SigPort. http://sigport.org/2552
, 2018. AN EFFICIENT TARGET LOCALIZATION ESTIMATOR FROM BISTATIC RANGE AND TDOA MEASUREMENTS IN MULTISTATIC RADAR. Available at: http://sigport.org/2552.
. (2018). "AN EFFICIENT TARGET LOCALIZATION ESTIMATOR FROM BISTATIC RANGE AND TDOA MEASUREMENTS IN MULTISTATIC RADAR." Web.
1. . AN EFFICIENT TARGET LOCALIZATION ESTIMATOR FROM BISTATIC RANGE AND TDOA MEASUREMENTS IN MULTISTATIC RADAR [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2552

FACTORIZED HIDDEN VARIABILITY LEARNING FOR ADAPTATION OF SHORT DURATION LANGUAGE IDENTIFICATION MODELS


Bidirectional long short term memory (BLSTM) recurrent neural networks (RNNs) have recently outperformed other state-of-the-art approaches, such as i-vector and deep neural networks (DNNs) in automatic language identification (LID), particularly when testing with very short utterances (∼3s). Mismatches conditions between training and test data, e.g. speaker, channel, duration and environmental noise, are a major source of performance degradation for LID.

POSTER.pdf

PDF icon POSTER.pdf (878 downloads)

Paper Details

Authors:
Sarith Fernando, Vidhyasaharan Sethu, Eliathamby Ambikairajah
Submitted On:
12 April 2018 - 9:48pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

POSTER.pdf

(878 downloads)

Subscribe

[1] Sarith Fernando, Vidhyasaharan Sethu, Eliathamby Ambikairajah, "FACTORIZED HIDDEN VARIABILITY LEARNING FOR ADAPTATION OF SHORT DURATION LANGUAGE IDENTIFICATION MODELS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2551. Accessed: Jul. 19, 2018.
@article{2551-18,
url = {http://sigport.org/2551},
author = {Sarith Fernando; Vidhyasaharan Sethu; Eliathamby Ambikairajah },
publisher = {IEEE SigPort},
title = {FACTORIZED HIDDEN VARIABILITY LEARNING FOR ADAPTATION OF SHORT DURATION LANGUAGE IDENTIFICATION MODELS},
year = {2018} }
TY - EJOUR
T1 - FACTORIZED HIDDEN VARIABILITY LEARNING FOR ADAPTATION OF SHORT DURATION LANGUAGE IDENTIFICATION MODELS
AU - Sarith Fernando; Vidhyasaharan Sethu; Eliathamby Ambikairajah
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2551
ER -
Sarith Fernando, Vidhyasaharan Sethu, Eliathamby Ambikairajah. (2018). FACTORIZED HIDDEN VARIABILITY LEARNING FOR ADAPTATION OF SHORT DURATION LANGUAGE IDENTIFICATION MODELS. IEEE SigPort. http://sigport.org/2551
Sarith Fernando, Vidhyasaharan Sethu, Eliathamby Ambikairajah, 2018. FACTORIZED HIDDEN VARIABILITY LEARNING FOR ADAPTATION OF SHORT DURATION LANGUAGE IDENTIFICATION MODELS. Available at: http://sigport.org/2551.
Sarith Fernando, Vidhyasaharan Sethu, Eliathamby Ambikairajah. (2018). "FACTORIZED HIDDEN VARIABILITY LEARNING FOR ADAPTATION OF SHORT DURATION LANGUAGE IDENTIFICATION MODELS." Web.
1. Sarith Fernando, Vidhyasaharan Sethu, Eliathamby Ambikairajah. FACTORIZED HIDDEN VARIABILITY LEARNING FOR ADAPTATION OF SHORT DURATION LANGUAGE IDENTIFICATION MODELS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2551

Speaker-Invariant Training via Adversarial Learning

Paper Details

Authors:
Zhong Meng, Jinyu Li, Zhuo Chen, Yong Zhao, Vadim Mazalov, Yifan Gong, Biing-Hwang (Fred) Juang
Submitted On:
12 April 2018 - 6:09pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

sit_poster.pptx

(29 downloads)

Subscribe

[1] Zhong Meng, Jinyu Li, Zhuo Chen, Yong Zhao, Vadim Mazalov, Yifan Gong, Biing-Hwang (Fred) Juang, "Speaker-Invariant Training via Adversarial Learning", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2508. Accessed: Jul. 19, 2018.
@article{2508-18,
url = {http://sigport.org/2508},
author = {Zhong Meng; Jinyu Li; Zhuo Chen; Yong Zhao; Vadim Mazalov; Yifan Gong; Biing-Hwang (Fred) Juang },
publisher = {IEEE SigPort},
title = {Speaker-Invariant Training via Adversarial Learning},
year = {2018} }
TY - EJOUR
T1 - Speaker-Invariant Training via Adversarial Learning
AU - Zhong Meng; Jinyu Li; Zhuo Chen; Yong Zhao; Vadim Mazalov; Yifan Gong; Biing-Hwang (Fred) Juang
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2508
ER -
Zhong Meng, Jinyu Li, Zhuo Chen, Yong Zhao, Vadim Mazalov, Yifan Gong, Biing-Hwang (Fred) Juang. (2018). Speaker-Invariant Training via Adversarial Learning. IEEE SigPort. http://sigport.org/2508
Zhong Meng, Jinyu Li, Zhuo Chen, Yong Zhao, Vadim Mazalov, Yifan Gong, Biing-Hwang (Fred) Juang, 2018. Speaker-Invariant Training via Adversarial Learning. Available at: http://sigport.org/2508.
Zhong Meng, Jinyu Li, Zhuo Chen, Yong Zhao, Vadim Mazalov, Yifan Gong, Biing-Hwang (Fred) Juang. (2018). "Speaker-Invariant Training via Adversarial Learning." Web.
1. Zhong Meng, Jinyu Li, Zhuo Chen, Yong Zhao, Vadim Mazalov, Yifan Gong, Biing-Hwang (Fred) Juang. Speaker-Invariant Training via Adversarial Learning [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2508

Adversarial Teacher-Student Learning for Unsupervised Adaptation

Paper Details

Authors:
Zhong Meng, Jinyu Li, Yifan Gong, Biing-Hwang (Fred) Juang
Submitted On:
12 April 2018 - 6:04pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ats_poster_v2.pptx

(31 downloads)

Subscribe

[1] Zhong Meng, Jinyu Li, Yifan Gong, Biing-Hwang (Fred) Juang, "Adversarial Teacher-Student Learning for Unsupervised Adaptation", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2506. Accessed: Jul. 19, 2018.
@article{2506-18,
url = {http://sigport.org/2506},
author = {Zhong Meng; Jinyu Li; Yifan Gong; Biing-Hwang (Fred) Juang },
publisher = {IEEE SigPort},
title = {Adversarial Teacher-Student Learning for Unsupervised Adaptation},
year = {2018} }
TY - EJOUR
T1 - Adversarial Teacher-Student Learning for Unsupervised Adaptation
AU - Zhong Meng; Jinyu Li; Yifan Gong; Biing-Hwang (Fred) Juang
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2506
ER -
Zhong Meng, Jinyu Li, Yifan Gong, Biing-Hwang (Fred) Juang. (2018). Adversarial Teacher-Student Learning for Unsupervised Adaptation. IEEE SigPort. http://sigport.org/2506
Zhong Meng, Jinyu Li, Yifan Gong, Biing-Hwang (Fred) Juang, 2018. Adversarial Teacher-Student Learning for Unsupervised Adaptation. Available at: http://sigport.org/2506.
Zhong Meng, Jinyu Li, Yifan Gong, Biing-Hwang (Fred) Juang. (2018). "Adversarial Teacher-Student Learning for Unsupervised Adaptation." Web.
1. Zhong Meng, Jinyu Li, Yifan Gong, Biing-Hwang (Fred) Juang. Adversarial Teacher-Student Learning for Unsupervised Adaptation [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2506

Speaker-Invariant Training via Adversarial Learning

Paper Details

Authors:
Zhong Meng, Jinyu Li, Zhuo Chen, Yong Zhao, Vadim Mazalov, Yifan Gong, Biing-Hwang (Fred) Juang
Submitted On:
12 April 2018 - 6:12pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

sit_poster.pptx

(31 downloads)

Subscribe

[1] Zhong Meng, Jinyu Li, Zhuo Chen, Yong Zhao, Vadim Mazalov, Yifan Gong, Biing-Hwang (Fred) Juang, "Speaker-Invariant Training via Adversarial Learning", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2505. Accessed: Jul. 19, 2018.
@article{2505-18,
url = {http://sigport.org/2505},
author = {Zhong Meng; Jinyu Li; Zhuo Chen; Yong Zhao; Vadim Mazalov; Yifan Gong; Biing-Hwang (Fred) Juang },
publisher = {IEEE SigPort},
title = {Speaker-Invariant Training via Adversarial Learning},
year = {2018} }
TY - EJOUR
T1 - Speaker-Invariant Training via Adversarial Learning
AU - Zhong Meng; Jinyu Li; Zhuo Chen; Yong Zhao; Vadim Mazalov; Yifan Gong; Biing-Hwang (Fred) Juang
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2505
ER -
Zhong Meng, Jinyu Li, Zhuo Chen, Yong Zhao, Vadim Mazalov, Yifan Gong, Biing-Hwang (Fred) Juang. (2018). Speaker-Invariant Training via Adversarial Learning. IEEE SigPort. http://sigport.org/2505
Zhong Meng, Jinyu Li, Zhuo Chen, Yong Zhao, Vadim Mazalov, Yifan Gong, Biing-Hwang (Fred) Juang, 2018. Speaker-Invariant Training via Adversarial Learning. Available at: http://sigport.org/2505.
Zhong Meng, Jinyu Li, Zhuo Chen, Yong Zhao, Vadim Mazalov, Yifan Gong, Biing-Hwang (Fred) Juang. (2018). "Speaker-Invariant Training via Adversarial Learning." Web.
1. Zhong Meng, Jinyu Li, Zhuo Chen, Yong Zhao, Vadim Mazalov, Yifan Gong, Biing-Hwang (Fred) Juang. Speaker-Invariant Training via Adversarial Learning [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2505

FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR


This paper proposes a method of controlling the dynamic range compressor using sound examples. Our earlier work showed the effectiveness of random forest regression to map acoustic features to effect control parameters. We extend this work to address the challenging task of extracting relevant features when audio events overlap. We assess differ- ent audio decomposition approaches such as onset event detection, NMF, and transient/stationary audio separation using ISTA and compare feature extraction strategies for each case.

Paper Details

Authors:
Di Sheng, Gyorgy Fazekas
Submitted On:
12 April 2018 - 1:40pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

poster_icassp.pdf

(373 downloads)

Subscribe

[1] Di Sheng, Gyorgy Fazekas, "FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2456. Accessed: Jul. 19, 2018.
@article{2456-18,
url = {http://sigport.org/2456},
author = {Di Sheng; Gyorgy Fazekas },
publisher = {IEEE SigPort},
title = {FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR},
year = {2018} }
TY - EJOUR
T1 - FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR
AU - Di Sheng; Gyorgy Fazekas
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2456
ER -
Di Sheng, Gyorgy Fazekas. (2018). FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR. IEEE SigPort. http://sigport.org/2456
Di Sheng, Gyorgy Fazekas, 2018. FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR. Available at: http://sigport.org/2456.
Di Sheng, Gyorgy Fazekas. (2018). "FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR." Web.
1. Di Sheng, Gyorgy Fazekas. FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2456

FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR


This paper proposes a method of controlling the dynamic range compressor using sound examples. Our earlier work showed the effectiveness of random forest regression to map acoustic features to effect control parameters. We extend this work to address the challenging task of extracting relevant features when audio events overlap. We assess differ- ent audio decomposition approaches such as onset event detection, NMF, and transient/stationary audio separation using ISTA and compare feature extraction strategies for each case.

Paper Details

Authors:
Di Sheng, Gyorgy Fazekas
Submitted On:
12 April 2018 - 1:40pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

poster_icassp.pdf

(373 downloads)

Subscribe

[1] Di Sheng, Gyorgy Fazekas, "FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2455. Accessed: Jul. 19, 2018.
@article{2455-18,
url = {http://sigport.org/2455},
author = {Di Sheng; Gyorgy Fazekas },
publisher = {IEEE SigPort},
title = {FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR},
year = {2018} }
TY - EJOUR
T1 - FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR
AU - Di Sheng; Gyorgy Fazekas
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2455
ER -
Di Sheng, Gyorgy Fazekas. (2018). FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR. IEEE SigPort. http://sigport.org/2455
Di Sheng, Gyorgy Fazekas, 2018. FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR. Available at: http://sigport.org/2455.
Di Sheng, Gyorgy Fazekas. (2018). "FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR." Web.
1. Di Sheng, Gyorgy Fazekas. FEATURE DESIGN USING AUDIO DECOMPOSITION FOR INTELLIGENT CONTROL OF THE DYNAMIC RANGE COMPRESSOR [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2455

Pages