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Loudspeaker and Microphone Array Signal Processing

Translation of a Higher Order Ambisonics Sound Scene Based on Parametric Decomposition


This paper presents a novel 3DoF+ system that allows to navigate, i.e., change position, in scene-based spatial audio content beyond the sweet spot of a Higher Order Ambisonics recording. It is one of the first such systems based on sound capturing at a single spatial position. The system uses a parametric decomposition of the recorded sound field. For the synthesis, only coarse distance information about the sources is needed as side information but not the exact number of them.

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Authors:
Andreas Behler, Peter Jax
Submitted On:
20 May 2020 - 10:32am
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[1] Andreas Behler, Peter Jax, "Translation of a Higher Order Ambisonics Sound Scene Based on Parametric Decomposition", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5414. Accessed: Jun. 07, 2020.
@article{5414-20,
url = {http://sigport.org/5414},
author = {Andreas Behler; Peter Jax },
publisher = {IEEE SigPort},
title = {Translation of a Higher Order Ambisonics Sound Scene Based on Parametric Decomposition},
year = {2020} }
TY - EJOUR
T1 - Translation of a Higher Order Ambisonics Sound Scene Based on Parametric Decomposition
AU - Andreas Behler; Peter Jax
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5414
ER -
Andreas Behler, Peter Jax. (2020). Translation of a Higher Order Ambisonics Sound Scene Based on Parametric Decomposition. IEEE SigPort. http://sigport.org/5414
Andreas Behler, Peter Jax, 2020. Translation of a Higher Order Ambisonics Sound Scene Based on Parametric Decomposition. Available at: http://sigport.org/5414.
Andreas Behler, Peter Jax. (2020). "Translation of a Higher Order Ambisonics Sound Scene Based on Parametric Decomposition." Web.
1. Andreas Behler, Peter Jax. Translation of a Higher Order Ambisonics Sound Scene Based on Parametric Decomposition [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5414

Evaluation of Sensor Self-Noise In Binaural Rendering of Spherical Microphone Array Signals


Spherical microphone arrays are used to capture spatial sound fields, which can then be rendered via headphones. We use the Real-Time Spherical Array Renderer (ReTiSAR) to analyze and auralize the propagation of sensor self-noise through the processing pipeline. An instrumental evaluation confirms a strong global influence of different array and rendering parameters on the spectral balance and the overall level of the rendered noise. The character of the noise is direction independent in the case of spatially uniformly distributed noise.

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13 May 2020 - 6:15pm
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Presentation Slides

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[1] , "Evaluation of Sensor Self-Noise In Binaural Rendering of Spherical Microphone Array Signals", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5162. Accessed: Jun. 07, 2020.
@article{5162-20,
url = {http://sigport.org/5162},
author = { },
publisher = {IEEE SigPort},
title = {Evaluation of Sensor Self-Noise In Binaural Rendering of Spherical Microphone Array Signals},
year = {2020} }
TY - EJOUR
T1 - Evaluation of Sensor Self-Noise In Binaural Rendering of Spherical Microphone Array Signals
AU -
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5162
ER -
. (2020). Evaluation of Sensor Self-Noise In Binaural Rendering of Spherical Microphone Array Signals. IEEE SigPort. http://sigport.org/5162
, 2020. Evaluation of Sensor Self-Noise In Binaural Rendering of Spherical Microphone Array Signals. Available at: http://sigport.org/5162.
. (2020). "Evaluation of Sensor Self-Noise In Binaural Rendering of Spherical Microphone Array Signals." Web.
1. . Evaluation of Sensor Self-Noise In Binaural Rendering of Spherical Microphone Array Signals [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5162

Acoustic Impulse Responses for Wearable Audio Devices


We present an open-access dataset of over 8000 acoustic impulse from 160 microphones spread across the body and affixed to wearable accessories. The data can be used to evaluate audio capture and array processing systems using wearable devices such as hearing aids, headphones, eyeglasses, jewelry, and clothing. We analyze the acoustic transfer functions

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Authors:
Ryan M. Corey, Naoki Tsuda, Andrew C. Singer
Submitted On:
11 May 2019 - 2:30pm
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corey_icassp2019_poster.pdf

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[1] Ryan M. Corey, Naoki Tsuda, Andrew C. Singer, "Acoustic Impulse Responses for Wearable Audio Devices", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4450. Accessed: Jun. 07, 2020.
@article{4450-19,
url = {http://sigport.org/4450},
author = {Ryan M. Corey; Naoki Tsuda; Andrew C. Singer },
publisher = {IEEE SigPort},
title = {Acoustic Impulse Responses for Wearable Audio Devices},
year = {2019} }
TY - EJOUR
T1 - Acoustic Impulse Responses for Wearable Audio Devices
AU - Ryan M. Corey; Naoki Tsuda; Andrew C. Singer
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4450
ER -
Ryan M. Corey, Naoki Tsuda, Andrew C. Singer. (2019). Acoustic Impulse Responses for Wearable Audio Devices. IEEE SigPort. http://sigport.org/4450
Ryan M. Corey, Naoki Tsuda, Andrew C. Singer, 2019. Acoustic Impulse Responses for Wearable Audio Devices. Available at: http://sigport.org/4450.
Ryan M. Corey, Naoki Tsuda, Andrew C. Singer. (2019). "Acoustic Impulse Responses for Wearable Audio Devices." Web.
1. Ryan M. Corey, Naoki Tsuda, Andrew C. Singer. Acoustic Impulse Responses for Wearable Audio Devices [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4450

Learning Dynamic Stream Weights for Linear Dynamical Systems using Natural Evolution Strategies


Multimodal data fusion is an important aspect of many object localization and tracking frameworks that rely on sensory observations from different sources. A prominent example is audiovisual speaker localization, where the incorporation of visual information has shown to benefit overall performance, especially in adverse acoustic conditions. Recently, the notion of dynamic stream weights as an efficient data fusion technique has been introduced into this field.

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10 May 2019 - 3:53am
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icassp2019_schymura.pdf

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[1] , "Learning Dynamic Stream Weights for Linear Dynamical Systems using Natural Evolution Strategies", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4283. Accessed: Jun. 07, 2020.
@article{4283-19,
url = {http://sigport.org/4283},
author = { },
publisher = {IEEE SigPort},
title = {Learning Dynamic Stream Weights for Linear Dynamical Systems using Natural Evolution Strategies},
year = {2019} }
TY - EJOUR
T1 - Learning Dynamic Stream Weights for Linear Dynamical Systems using Natural Evolution Strategies
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4283
ER -
. (2019). Learning Dynamic Stream Weights for Linear Dynamical Systems using Natural Evolution Strategies. IEEE SigPort. http://sigport.org/4283
, 2019. Learning Dynamic Stream Weights for Linear Dynamical Systems using Natural Evolution Strategies. Available at: http://sigport.org/4283.
. (2019). "Learning Dynamic Stream Weights for Linear Dynamical Systems using Natural Evolution Strategies." Web.
1. . Learning Dynamic Stream Weights for Linear Dynamical Systems using Natural Evolution Strategies [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4283

MIRAGE: 2D sound source localization using microphone pair augmentation with echoes


It is commonly observed that acoustic echoes hurt perfor-mance of sound source localization (SSL) methods. We in-troduce the concept of microphone array augmentation withechoes (MIRAGE) and show how estimation of early-echocharacteristics can in fact benefit SSL. We propose a learning-based scheme for echo estimation combined with a physics-based scheme for echo aggregation.

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Authors:
Diego Di Carlo, Antoine Deleforge, Nancy Bertin
Submitted On:
9 May 2019 - 3:34am
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Poster

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[1] Diego Di Carlo, Antoine Deleforge, Nancy Bertin, "MIRAGE: 2D sound source localization using microphone pair augmentation with echoes", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4164. Accessed: Jun. 07, 2020.
@article{4164-19,
url = {http://sigport.org/4164},
author = {Diego Di Carlo; Antoine Deleforge; Nancy Bertin },
publisher = {IEEE SigPort},
title = {MIRAGE: 2D sound source localization using microphone pair augmentation with echoes},
year = {2019} }
TY - EJOUR
T1 - MIRAGE: 2D sound source localization using microphone pair augmentation with echoes
AU - Diego Di Carlo; Antoine Deleforge; Nancy Bertin
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4164
ER -
Diego Di Carlo, Antoine Deleforge, Nancy Bertin. (2019). MIRAGE: 2D sound source localization using microphone pair augmentation with echoes. IEEE SigPort. http://sigport.org/4164
Diego Di Carlo, Antoine Deleforge, Nancy Bertin, 2019. MIRAGE: 2D sound source localization using microphone pair augmentation with echoes. Available at: http://sigport.org/4164.
Diego Di Carlo, Antoine Deleforge, Nancy Bertin. (2019). "MIRAGE: 2D sound source localization using microphone pair augmentation with echoes." Web.
1. Diego Di Carlo, Antoine Deleforge, Nancy Bertin. MIRAGE: 2D sound source localization using microphone pair augmentation with echoes [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4164

Robust gridless sound field decomposition based on structured eciprocity gap functional in spherical harmonic domain


A sound field reconstruction method for a region including sources is proposed. Under the assumption of spatial sparsity of the sources,this reconstruction problem has been solved by using sparse decomposition algorithms with the discretization of the target region. Since this discretization leads to the off-grid problem, we previously proposed a gridless sound field decomposition method based on the reciprocity gap functional in the spherical harmonic domain.

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Authors:
Yuhta Takida, Shoichi Koyama, Natsuki Ueno, Hiroshi Saruwatari
Submitted On:
8 May 2019 - 6:39am
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[1] Yuhta Takida, Shoichi Koyama, Natsuki Ueno, Hiroshi Saruwatari, "Robust gridless sound field decomposition based on structured eciprocity gap functional in spherical harmonic domain", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4069. Accessed: Jun. 07, 2020.
@article{4069-19,
url = {http://sigport.org/4069},
author = {Yuhta Takida; Shoichi Koyama; Natsuki Ueno; Hiroshi Saruwatari },
publisher = {IEEE SigPort},
title = {Robust gridless sound field decomposition based on structured eciprocity gap functional in spherical harmonic domain},
year = {2019} }
TY - EJOUR
T1 - Robust gridless sound field decomposition based on structured eciprocity gap functional in spherical harmonic domain
AU - Yuhta Takida; Shoichi Koyama; Natsuki Ueno; Hiroshi Saruwatari
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4069
ER -
Yuhta Takida, Shoichi Koyama, Natsuki Ueno, Hiroshi Saruwatari. (2019). Robust gridless sound field decomposition based on structured eciprocity gap functional in spherical harmonic domain. IEEE SigPort. http://sigport.org/4069
Yuhta Takida, Shoichi Koyama, Natsuki Ueno, Hiroshi Saruwatari, 2019. Robust gridless sound field decomposition based on structured eciprocity gap functional in spherical harmonic domain. Available at: http://sigport.org/4069.
Yuhta Takida, Shoichi Koyama, Natsuki Ueno, Hiroshi Saruwatari. (2019). "Robust gridless sound field decomposition based on structured eciprocity gap functional in spherical harmonic domain." Web.
1. Yuhta Takida, Shoichi Koyama, Natsuki Ueno, Hiroshi Saruwatari. Robust gridless sound field decomposition based on structured eciprocity gap functional in spherical harmonic domain [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4069

Poster of ICASSP 2019 Paper #4469

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Authors:
Qing Wang, Xian Wang, Tongdong Dou, Hua Chen, Xiaohuan Wu
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7 May 2019 - 10:54pm
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poster of paper #4469

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[1] Qing Wang, Xian Wang, Tongdong Dou, Hua Chen, Xiaohuan Wu, "Poster of ICASSP 2019 Paper #4469", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3992. Accessed: Jun. 07, 2020.
@article{3992-19,
url = {http://sigport.org/3992},
author = {Qing Wang; Xian Wang; Tongdong Dou; Hua Chen; Xiaohuan Wu },
publisher = {IEEE SigPort},
title = {Poster of ICASSP 2019 Paper #4469},
year = {2019} }
TY - EJOUR
T1 - Poster of ICASSP 2019 Paper #4469
AU - Qing Wang; Xian Wang; Tongdong Dou; Hua Chen; Xiaohuan Wu
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3992
ER -
Qing Wang, Xian Wang, Tongdong Dou, Hua Chen, Xiaohuan Wu. (2019). Poster of ICASSP 2019 Paper #4469. IEEE SigPort. http://sigport.org/3992
Qing Wang, Xian Wang, Tongdong Dou, Hua Chen, Xiaohuan Wu, 2019. Poster of ICASSP 2019 Paper #4469. Available at: http://sigport.org/3992.
Qing Wang, Xian Wang, Tongdong Dou, Hua Chen, Xiaohuan Wu. (2019). "Poster of ICASSP 2019 Paper #4469." Web.
1. Qing Wang, Xian Wang, Tongdong Dou, Hua Chen, Xiaohuan Wu. Poster of ICASSP 2019 Paper #4469 [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3992

PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE


The problem of higher order sound field capture with spherical microphone arrays is considered. While A-format cardioid designs are commonplace for first order capture, interest remains in the increased spatial resolution delivered by higher order arrays. Spherical arrays typically use omnidirectional microphones mounted on a rigid baffle, from which higher order spatial components are estimated by accounting for radial mode strength.

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7 May 2019 - 12:54pm
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Dual Open Sphere Microphone Arrays.pdf

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[1] , "PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3922. Accessed: Jun. 07, 2020.
@article{3922-19,
url = {http://sigport.org/3922},
author = { },
publisher = {IEEE SigPort},
title = {PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE},
year = {2019} }
TY - EJOUR
T1 - PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3922
ER -
. (2019). PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE. IEEE SigPort. http://sigport.org/3922
, 2019. PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE. Available at: http://sigport.org/3922.
. (2019). "PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE." Web.
1. . PRACTICAL CONCENTRIC OPEN SPHERE CARDIOID MICROPHONE ARRAY DESIGN FOR HIGHER ORDER SOUND FIELD CAPTURE [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3922

Combining Artificial and Natural Background Noise in Personal Audio Systems


Personal audio systems are designed to deliver spatially separated regions of audio to individual listeners. This paper presents a method for improving the privacy of such systems. The level of a synthetic masking signal is optimised to provide specified levels of intelligibility in the bright and dark sound zones and reduce the potential for annoyance of listeners
in the dark zone by responding to changes in ambient noise.

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Authors:
Daniel Wallace, Jordan Cheer
Submitted On:
16 July 2018 - 5:14am
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Presentation given at SAM 2018

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[1] Daniel Wallace, Jordan Cheer, "Combining Artificial and Natural Background Noise in Personal Audio Systems", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3380. Accessed: Jun. 07, 2020.
@article{3380-18,
url = {http://sigport.org/3380},
author = {Daniel Wallace; Jordan Cheer },
publisher = {IEEE SigPort},
title = {Combining Artificial and Natural Background Noise in Personal Audio Systems},
year = {2018} }
TY - EJOUR
T1 - Combining Artificial and Natural Background Noise in Personal Audio Systems
AU - Daniel Wallace; Jordan Cheer
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3380
ER -
Daniel Wallace, Jordan Cheer. (2018). Combining Artificial and Natural Background Noise in Personal Audio Systems. IEEE SigPort. http://sigport.org/3380
Daniel Wallace, Jordan Cheer, 2018. Combining Artificial and Natural Background Noise in Personal Audio Systems. Available at: http://sigport.org/3380.
Daniel Wallace, Jordan Cheer. (2018). "Combining Artificial and Natural Background Noise in Personal Audio Systems." Web.
1. Daniel Wallace, Jordan Cheer. Combining Artificial and Natural Background Noise in Personal Audio Systems [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3380

Direction of Arrival Estimation with Microphone Arrays Using SRP-PHAT and Neural Networks


The Steered Response Power with phase transform (SRP-PHAT) is one of the most employed techniques for Direction of Arrival (DOA) estimation with microphone arrays due its robustness against acoustical conditions as reverberation or noise. Among its main drawbacks is the growth of its computational complexity when the search space increases. To solve this issue, we propose the use of Neural Networks (NN) to obtain the DOA as a regression problem from a low resolution SRP-PHAT power map.

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Authors:
Jose Ramon Beltran
Submitted On:
3 July 2018 - 5:28am
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Poster

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[1] Jose Ramon Beltran, "Direction of Arrival Estimation with Microphone Arrays Using SRP-PHAT and Neural Networks", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3350. Accessed: Jun. 07, 2020.
@article{3350-18,
url = {http://sigport.org/3350},
author = {Jose Ramon Beltran },
publisher = {IEEE SigPort},
title = {Direction of Arrival Estimation with Microphone Arrays Using SRP-PHAT and Neural Networks},
year = {2018} }
TY - EJOUR
T1 - Direction of Arrival Estimation with Microphone Arrays Using SRP-PHAT and Neural Networks
AU - Jose Ramon Beltran
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3350
ER -
Jose Ramon Beltran. (2018). Direction of Arrival Estimation with Microphone Arrays Using SRP-PHAT and Neural Networks. IEEE SigPort. http://sigport.org/3350
Jose Ramon Beltran, 2018. Direction of Arrival Estimation with Microphone Arrays Using SRP-PHAT and Neural Networks. Available at: http://sigport.org/3350.
Jose Ramon Beltran. (2018). "Direction of Arrival Estimation with Microphone Arrays Using SRP-PHAT and Neural Networks." Web.
1. Jose Ramon Beltran. Direction of Arrival Estimation with Microphone Arrays Using SRP-PHAT and Neural Networks [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3350

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