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Room Acoustics and Acoustic System Modeling

INFRASONIC SCENE FINGERPRINTING FOR AUTHENTICATING SPEAKER LOCATION


Ambient infrasound with frequency ranges well below 20 Hz is known to carry robust navigation cues that can be exploited to authenticate the location of a speaker. Unfortunately, many of the mobile devices like smartphones have been optimized to work in the human auditory range, thereby suppressing information in the infrasonic region. In this paper, we show that these ultra-low frequency cues can still be extracted from a standard smartphone recording by using acceleration-based cepstral features.

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Authors:
Kenji Aono, Shantanu Chakrabartty, Toshihiko Yamasaki
Submitted On:
14 March 2017 - 7:06pm
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ICASSP-2017_AASP-P3.5.pdf

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[1] Kenji Aono, Shantanu Chakrabartty, Toshihiko Yamasaki, "INFRASONIC SCENE FINGERPRINTING FOR AUTHENTICATING SPEAKER LOCATION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1766. Accessed: Apr. 25, 2017.
@article{1766-17,
url = {http://sigport.org/1766},
author = {Kenji Aono; Shantanu Chakrabartty; Toshihiko Yamasaki },
publisher = {IEEE SigPort},
title = {INFRASONIC SCENE FINGERPRINTING FOR AUTHENTICATING SPEAKER LOCATION},
year = {2017} }
TY - EJOUR
T1 - INFRASONIC SCENE FINGERPRINTING FOR AUTHENTICATING SPEAKER LOCATION
AU - Kenji Aono; Shantanu Chakrabartty; Toshihiko Yamasaki
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1766
ER -
Kenji Aono, Shantanu Chakrabartty, Toshihiko Yamasaki. (2017). INFRASONIC SCENE FINGERPRINTING FOR AUTHENTICATING SPEAKER LOCATION. IEEE SigPort. http://sigport.org/1766
Kenji Aono, Shantanu Chakrabartty, Toshihiko Yamasaki, 2017. INFRASONIC SCENE FINGERPRINTING FOR AUTHENTICATING SPEAKER LOCATION. Available at: http://sigport.org/1766.
Kenji Aono, Shantanu Chakrabartty, Toshihiko Yamasaki. (2017). "INFRASONIC SCENE FINGERPRINTING FOR AUTHENTICATING SPEAKER LOCATION." Web.
1. Kenji Aono, Shantanu Chakrabartty, Toshihiko Yamasaki. INFRASONIC SCENE FINGERPRINTING FOR AUTHENTICATING SPEAKER LOCATION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1766

CONFIDENCE MEASURES FOR CTC-BASED PHONE SYNCHRONOUS DECODING

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6 March 2017 - 4:49pm
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psdcm icassp2017 oral slides_zhc00.pdf

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[1] , "CONFIDENCE MEASURES FOR CTC-BASED PHONE SYNCHRONOUS DECODING", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1668. Accessed: Apr. 25, 2017.
@article{1668-17,
url = {http://sigport.org/1668},
author = { },
publisher = {IEEE SigPort},
title = {CONFIDENCE MEASURES FOR CTC-BASED PHONE SYNCHRONOUS DECODING},
year = {2017} }
TY - EJOUR
T1 - CONFIDENCE MEASURES FOR CTC-BASED PHONE SYNCHRONOUS DECODING
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1668
ER -
. (2017). CONFIDENCE MEASURES FOR CTC-BASED PHONE SYNCHRONOUS DECODING. IEEE SigPort. http://sigport.org/1668
, 2017. CONFIDENCE MEASURES FOR CTC-BASED PHONE SYNCHRONOUS DECODING. Available at: http://sigport.org/1668.
. (2017). "CONFIDENCE MEASURES FOR CTC-BASED PHONE SYNCHRONOUS DECODING." Web.
1. . CONFIDENCE MEASURES FOR CTC-BASED PHONE SYNCHRONOUS DECODING [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1668

RECURRENT CONVOLUTIONAL NEURAL NETWORK FOR SPEECH PROCESSING


Different neural networks have exhibited excellent performance on various speech processing tasks, and they usually have specific advantages and disadvantages. We propose to use a recently developed deep learning model, recurrent convolutional neural network (RCNN), for speech processing, which inherits some merits of recurrent neural network (RNN) and convolutional neural network (CNN). The core module can be viewed as a convolutional layer embedded with an RNN, which enables the model to capture both temporal and frequency dependence in the spectrogram of the speech in an efficient way.

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Authors:
Yue Zhao, Xingyu Jin, Xiaolin Hu
Submitted On:
5 March 2017 - 10:18am
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icassp2017_poster.pptx

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[1] Yue Zhao, Xingyu Jin, Xiaolin Hu, "RECURRENT CONVOLUTIONAL NEURAL NETWORK FOR SPEECH PROCESSING", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1632. Accessed: Apr. 25, 2017.
@article{1632-17,
url = {http://sigport.org/1632},
author = {Yue Zhao; Xingyu Jin; Xiaolin Hu },
publisher = {IEEE SigPort},
title = {RECURRENT CONVOLUTIONAL NEURAL NETWORK FOR SPEECH PROCESSING},
year = {2017} }
TY - EJOUR
T1 - RECURRENT CONVOLUTIONAL NEURAL NETWORK FOR SPEECH PROCESSING
AU - Yue Zhao; Xingyu Jin; Xiaolin Hu
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1632
ER -
Yue Zhao, Xingyu Jin, Xiaolin Hu. (2017). RECURRENT CONVOLUTIONAL NEURAL NETWORK FOR SPEECH PROCESSING. IEEE SigPort. http://sigport.org/1632
Yue Zhao, Xingyu Jin, Xiaolin Hu, 2017. RECURRENT CONVOLUTIONAL NEURAL NETWORK FOR SPEECH PROCESSING. Available at: http://sigport.org/1632.
Yue Zhao, Xingyu Jin, Xiaolin Hu. (2017). "RECURRENT CONVOLUTIONAL NEURAL NETWORK FOR SPEECH PROCESSING." Web.
1. Yue Zhao, Xingyu Jin, Xiaolin Hu. RECURRENT CONVOLUTIONAL NEURAL NETWORK FOR SPEECH PROCESSING [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1632

Unsupervised Speaker Adaptation of BLSTM-RNN for LVCSR Based on Speaker Code


Recently, the speaker code based adaptation has been successfully expanded to recurrent neural networks using bidirectional Long Short-Term Memory (BLSTM-RNN) [1]. Experiments on the small-scale TIMIT task have demonstrated that the speaker code based adaptation is also valid for BLSTM-RNN. In this paper, we evaluate this method on large-scale task and introduce an error normalization method to balance the back-propagation errors derived from different layers for speaker codes. Meanwhile, we use singular value decomposition (SVD) method to conduct model compression.

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Authors:
Zhiying Huang, Shaofei Xue, Zhijie Yan, Lirong Dai
Submitted On:
14 October 2016 - 10:15am
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ISCSLP_presentation_ZhiyingHuang_upload.pdf

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[1] Zhiying Huang, Shaofei Xue, Zhijie Yan, Lirong Dai, "Unsupervised Speaker Adaptation of BLSTM-RNN for LVCSR Based on Speaker Code", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1198. Accessed: Apr. 25, 2017.
@article{1198-16,
url = {http://sigport.org/1198},
author = {Zhiying Huang; Shaofei Xue; Zhijie Yan; Lirong Dai },
publisher = {IEEE SigPort},
title = {Unsupervised Speaker Adaptation of BLSTM-RNN for LVCSR Based on Speaker Code},
year = {2016} }
TY - EJOUR
T1 - Unsupervised Speaker Adaptation of BLSTM-RNN for LVCSR Based on Speaker Code
AU - Zhiying Huang; Shaofei Xue; Zhijie Yan; Lirong Dai
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1198
ER -
Zhiying Huang, Shaofei Xue, Zhijie Yan, Lirong Dai. (2016). Unsupervised Speaker Adaptation of BLSTM-RNN for LVCSR Based on Speaker Code. IEEE SigPort. http://sigport.org/1198
Zhiying Huang, Shaofei Xue, Zhijie Yan, Lirong Dai, 2016. Unsupervised Speaker Adaptation of BLSTM-RNN for LVCSR Based on Speaker Code. Available at: http://sigport.org/1198.
Zhiying Huang, Shaofei Xue, Zhijie Yan, Lirong Dai. (2016). "Unsupervised Speaker Adaptation of BLSTM-RNN for LVCSR Based on Speaker Code." Web.
1. Zhiying Huang, Shaofei Xue, Zhijie Yan, Lirong Dai. Unsupervised Speaker Adaptation of BLSTM-RNN for LVCSR Based on Speaker Code [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1198

Multichannel identification of room acoustic systems with adaptive filters based on orthonormal basis functions

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Authors:
Vairetti G., De Sena E., Catrysse M., Jensen S.H., Moonen M., van Waterschoot T.
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24 March 2016 - 3:09am
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ICASSP2016_Vairetti_1904.pdf

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[1] Vairetti G., De Sena E., Catrysse M., Jensen S.H., Moonen M., van Waterschoot T., "Multichannel identification of room acoustic systems with adaptive filters based on orthonormal basis functions", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1019. Accessed: Apr. 25, 2017.
@article{1019-16,
url = {http://sigport.org/1019},
author = {Vairetti G.; De Sena E.; Catrysse M.; Jensen S.H.; Moonen M.; van Waterschoot T. },
publisher = {IEEE SigPort},
title = {Multichannel identification of room acoustic systems with adaptive filters based on orthonormal basis functions},
year = {2016} }
TY - EJOUR
T1 - Multichannel identification of room acoustic systems with adaptive filters based on orthonormal basis functions
AU - Vairetti G.; De Sena E.; Catrysse M.; Jensen S.H.; Moonen M.; van Waterschoot T.
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1019
ER -
Vairetti G., De Sena E., Catrysse M., Jensen S.H., Moonen M., van Waterschoot T.. (2016). Multichannel identification of room acoustic systems with adaptive filters based on orthonormal basis functions. IEEE SigPort. http://sigport.org/1019
Vairetti G., De Sena E., Catrysse M., Jensen S.H., Moonen M., van Waterschoot T., 2016. Multichannel identification of room acoustic systems with adaptive filters based on orthonormal basis functions. Available at: http://sigport.org/1019.
Vairetti G., De Sena E., Catrysse M., Jensen S.H., Moonen M., van Waterschoot T.. (2016). "Multichannel identification of room acoustic systems with adaptive filters based on orthonormal basis functions." Web.
1. Vairetti G., De Sena E., Catrysse M., Jensen S.H., Moonen M., van Waterschoot T.. Multichannel identification of room acoustic systems with adaptive filters based on orthonormal basis functions [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1019

ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT

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Authors:
Marco Crocco, Alessio Del Bue
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19 March 2016 - 11:29am
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2016_ICASSP_poster.pdf

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[1] Marco Crocco, Alessio Del Bue, "ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/819. Accessed: Apr. 25, 2017.
@article{819-16,
url = {http://sigport.org/819},
author = {Marco Crocco; Alessio Del Bue },
publisher = {IEEE SigPort},
title = {ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT},
year = {2016} }
TY - EJOUR
T1 - ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT
AU - Marco Crocco; Alessio Del Bue
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/819
ER -
Marco Crocco, Alessio Del Bue. (2016). ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT. IEEE SigPort. http://sigport.org/819
Marco Crocco, Alessio Del Bue, 2016. ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT. Available at: http://sigport.org/819.
Marco Crocco, Alessio Del Bue. (2016). "ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT." Web.
1. Marco Crocco, Alessio Del Bue. ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/819

ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT

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Authors:
Marco Crocco, Alessio Del Bue
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19 March 2016 - 11:29am
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2016_ICASSP_poster.pdf

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[1] Marco Crocco, Alessio Del Bue, "ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/818. Accessed: Apr. 25, 2017.
@article{818-16,
url = {http://sigport.org/818},
author = {Marco Crocco; Alessio Del Bue },
publisher = {IEEE SigPort},
title = {ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT},
year = {2016} }
TY - EJOUR
T1 - ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT
AU - Marco Crocco; Alessio Del Bue
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/818
ER -
Marco Crocco, Alessio Del Bue. (2016). ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT. IEEE SigPort. http://sigport.org/818
Marco Crocco, Alessio Del Bue, 2016. ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT. Available at: http://sigport.org/818.
Marco Crocco, Alessio Del Bue. (2016). "ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT." Web.
1. Marco Crocco, Alessio Del Bue. ESTIMATION OF TDOA FOR ROOM REFLECTIONS BY ITERATIVE WEIGHTED L1 CONSTRAINT [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/818

Characterization and Classification of Sonar Targets Using Ellipsoid Features


We present a geometry-inspired characterization of
target response for active sonar that exploits similarity between
intra-class features to distinguish between different targets
against environmental objects such as a rock. Key innovation is to
represent feature manifolds as a set of ellipsoids, each of which
geometrically encompasses a unique physical characteristic of
the target’s response. We have demonstrated over experimental
field data that for a given target class, these feature ellipsoids

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Authors:
Ananya Sen Gupta, Ivars Kirsteins
Submitted On:
23 February 2016 - 1:44pm
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globalSIP_slides_final3.pdf

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globalSIP_slides_final3.pdf

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[1] Ananya Sen Gupta, Ivars Kirsteins, "Characterization and Classification of Sonar Targets Using Ellipsoid Features", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/507. Accessed: Apr. 25, 2017.
@article{507-15,
url = {http://sigport.org/507},
author = {Ananya Sen Gupta; Ivars Kirsteins },
publisher = {IEEE SigPort},
title = {Characterization and Classification of Sonar Targets Using Ellipsoid Features},
year = {2015} }
TY - EJOUR
T1 - Characterization and Classification of Sonar Targets Using Ellipsoid Features
AU - Ananya Sen Gupta; Ivars Kirsteins
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/507
ER -
Ananya Sen Gupta, Ivars Kirsteins. (2015). Characterization and Classification of Sonar Targets Using Ellipsoid Features. IEEE SigPort. http://sigport.org/507
Ananya Sen Gupta, Ivars Kirsteins, 2015. Characterization and Classification of Sonar Targets Using Ellipsoid Features. Available at: http://sigport.org/507.
Ananya Sen Gupta, Ivars Kirsteins. (2015). "Characterization and Classification of Sonar Targets Using Ellipsoid Features." Web.
1. Ananya Sen Gupta, Ivars Kirsteins. Characterization and Classification of Sonar Targets Using Ellipsoid Features [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/507

Room Shape Reconstruction With a Single Mobile Acoustic Sensor

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Authors:
TIEXING WANG, BIAO CHEN
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23 February 2016 - 1:44pm
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globalsip2015.pdf

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[1] TIEXING WANG, BIAO CHEN, "Room Shape Reconstruction With a Single Mobile Acoustic Sensor", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/415. Accessed: Apr. 25, 2017.
@article{415-15,
url = {http://sigport.org/415},
author = {TIEXING WANG; BIAO CHEN },
publisher = {IEEE SigPort},
title = {Room Shape Reconstruction With a Single Mobile Acoustic Sensor},
year = {2015} }
TY - EJOUR
T1 - Room Shape Reconstruction With a Single Mobile Acoustic Sensor
AU - TIEXING WANG; BIAO CHEN
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/415
ER -
TIEXING WANG, BIAO CHEN. (2015). Room Shape Reconstruction With a Single Mobile Acoustic Sensor. IEEE SigPort. http://sigport.org/415
TIEXING WANG, BIAO CHEN, 2015. Room Shape Reconstruction With a Single Mobile Acoustic Sensor. Available at: http://sigport.org/415.
TIEXING WANG, BIAO CHEN. (2015). "Room Shape Reconstruction With a Single Mobile Acoustic Sensor." Web.
1. TIEXING WANG, BIAO CHEN. Room Shape Reconstruction With a Single Mobile Acoustic Sensor [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/415

Natural Sound Rendering for Headphones: Integration of signal processing techniques


With the strong growth of assistive and personal listening devices, natural sound rendering over headphones is becoming a necessity for prolonged listening in multimedia and virtual reality applications. The aim of natural sound rendering is to naturally recreate the sound scenes with the spatial and timbral quality as natural as possible, so as to achieve a truly immersive listening experience. However, rendering natural sound over headphones encounters many challenges. This tutorial article presents signal processing techniques to tackle these challenges to assist human listening.

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Authors:
Kaushik Sunder, Ee-Leng Tan
Submitted On:
23 February 2016 - 1:44pm
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Type:

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SPM2015manuscript-Natural Sound Rendering for Headphones.pdf

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[1] Kaushik Sunder, Ee-Leng Tan, "Natural Sound Rendering for Headphones: Integration of signal processing techniques", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/166. Accessed: Apr. 25, 2017.
@article{166-15,
url = {http://sigport.org/166},
author = {Kaushik Sunder; Ee-Leng Tan },
publisher = {IEEE SigPort},
title = {Natural Sound Rendering for Headphones: Integration of signal processing techniques},
year = {2015} }
TY - EJOUR
T1 - Natural Sound Rendering for Headphones: Integration of signal processing techniques
AU - Kaushik Sunder; Ee-Leng Tan
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/166
ER -
Kaushik Sunder, Ee-Leng Tan. (2015). Natural Sound Rendering for Headphones: Integration of signal processing techniques. IEEE SigPort. http://sigport.org/166
Kaushik Sunder, Ee-Leng Tan, 2015. Natural Sound Rendering for Headphones: Integration of signal processing techniques. Available at: http://sigport.org/166.
Kaushik Sunder, Ee-Leng Tan. (2015). "Natural Sound Rendering for Headphones: Integration of signal processing techniques." Web.
1. Kaushik Sunder, Ee-Leng Tan. Natural Sound Rendering for Headphones: Integration of signal processing techniques [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/166