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Audio and Acoustic Signal Processing

Distributed Maximum Likelihood using Dynamic Average Consensus


This paper presents the formulation and analysis of a novel distributed maximum likelihood algorithm that utilizes a first-order optimization scheme. The proposed approach utilizes a static average consensus algorithm to reach agreement on the initial condition to the iterative optimization scheme and a dynamic average consensus algorithm to reach agreement on the gradient direction. The current distributed algorithm is guaranteed to exponentially recover the performance of the centralized algorithm.

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19 April 2018 - 2:52pm
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George_ICASSP_v1.pdf

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[1] , "Distributed Maximum Likelihood using Dynamic Average Consensus", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3003. Accessed: Nov. 19, 2018.
@article{3003-18,
url = {http://sigport.org/3003},
author = { },
publisher = {IEEE SigPort},
title = {Distributed Maximum Likelihood using Dynamic Average Consensus},
year = {2018} }
TY - EJOUR
T1 - Distributed Maximum Likelihood using Dynamic Average Consensus
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3003
ER -
. (2018). Distributed Maximum Likelihood using Dynamic Average Consensus. IEEE SigPort. http://sigport.org/3003
, 2018. Distributed Maximum Likelihood using Dynamic Average Consensus. Available at: http://sigport.org/3003.
. (2018). "Distributed Maximum Likelihood using Dynamic Average Consensus." Web.
1. . Distributed Maximum Likelihood using Dynamic Average Consensus [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3003

END-TO-END NEURAL NETWORK BASED AUTOMATED SPEECH SCORING

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Authors:
Lei Chen, Jidong Tao, Shabnam Ghaffarzadegan, Yao Qian
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19 April 2018 - 2:45pm
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icassp2018_final.pdf

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[1] Lei Chen, Jidong Tao, Shabnam Ghaffarzadegan, Yao Qian, "END-TO-END NEURAL NETWORK BASED AUTOMATED SPEECH SCORING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2999. Accessed: Nov. 19, 2018.
@article{2999-18,
url = {http://sigport.org/2999},
author = {Lei Chen; Jidong Tao; Shabnam Ghaffarzadegan; Yao Qian },
publisher = {IEEE SigPort},
title = {END-TO-END NEURAL NETWORK BASED AUTOMATED SPEECH SCORING},
year = {2018} }
TY - EJOUR
T1 - END-TO-END NEURAL NETWORK BASED AUTOMATED SPEECH SCORING
AU - Lei Chen; Jidong Tao; Shabnam Ghaffarzadegan; Yao Qian
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2999
ER -
Lei Chen, Jidong Tao, Shabnam Ghaffarzadegan, Yao Qian. (2018). END-TO-END NEURAL NETWORK BASED AUTOMATED SPEECH SCORING. IEEE SigPort. http://sigport.org/2999
Lei Chen, Jidong Tao, Shabnam Ghaffarzadegan, Yao Qian, 2018. END-TO-END NEURAL NETWORK BASED AUTOMATED SPEECH SCORING. Available at: http://sigport.org/2999.
Lei Chen, Jidong Tao, Shabnam Ghaffarzadegan, Yao Qian. (2018). "END-TO-END NEURAL NETWORK BASED AUTOMATED SPEECH SCORING." Web.
1. Lei Chen, Jidong Tao, Shabnam Ghaffarzadegan, Yao Qian. END-TO-END NEURAL NETWORK BASED AUTOMATED SPEECH SCORING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2999

MULTIPLE-MODEL AND REDUCED-ORDER KALMAN FILTERING FOR PATHOLOGICAL HAND TREMOR EXTRACTION

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Authors:
Vahid Khorasani Ghassab, Arash Mohammadi, Seyed Farokh Atashzar, Rajni V. Patel
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19 April 2018 - 2:34pm
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ICASSP_v1.pdf

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[1] Vahid Khorasani Ghassab, Arash Mohammadi, Seyed Farokh Atashzar, Rajni V. Patel, "MULTIPLE-MODEL AND REDUCED-ORDER KALMAN FILTERING FOR PATHOLOGICAL HAND TREMOR EXTRACTION", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2993. Accessed: Nov. 19, 2018.
@article{2993-18,
url = {http://sigport.org/2993},
author = {Vahid Khorasani Ghassab; Arash Mohammadi; Seyed Farokh Atashzar; Rajni V. Patel },
publisher = {IEEE SigPort},
title = {MULTIPLE-MODEL AND REDUCED-ORDER KALMAN FILTERING FOR PATHOLOGICAL HAND TREMOR EXTRACTION},
year = {2018} }
TY - EJOUR
T1 - MULTIPLE-MODEL AND REDUCED-ORDER KALMAN FILTERING FOR PATHOLOGICAL HAND TREMOR EXTRACTION
AU - Vahid Khorasani Ghassab; Arash Mohammadi; Seyed Farokh Atashzar; Rajni V. Patel
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2993
ER -
Vahid Khorasani Ghassab, Arash Mohammadi, Seyed Farokh Atashzar, Rajni V. Patel. (2018). MULTIPLE-MODEL AND REDUCED-ORDER KALMAN FILTERING FOR PATHOLOGICAL HAND TREMOR EXTRACTION. IEEE SigPort. http://sigport.org/2993
Vahid Khorasani Ghassab, Arash Mohammadi, Seyed Farokh Atashzar, Rajni V. Patel, 2018. MULTIPLE-MODEL AND REDUCED-ORDER KALMAN FILTERING FOR PATHOLOGICAL HAND TREMOR EXTRACTION. Available at: http://sigport.org/2993.
Vahid Khorasani Ghassab, Arash Mohammadi, Seyed Farokh Atashzar, Rajni V. Patel. (2018). "MULTIPLE-MODEL AND REDUCED-ORDER KALMAN FILTERING FOR PATHOLOGICAL HAND TREMOR EXTRACTION." Web.
1. Vahid Khorasani Ghassab, Arash Mohammadi, Seyed Farokh Atashzar, Rajni V. Patel. MULTIPLE-MODEL AND REDUCED-ORDER KALMAN FILTERING FOR PATHOLOGICAL HAND TREMOR EXTRACTION [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2993

Joint Transfer Subspace Learning and Feature Selection for Cross-corpus Speech Emotion Recognition

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Authors:
Peng Song, Wenming Zheng, Shifeng Ou,Yun Jin, Wenming Ma, Yanwei Yu
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19 April 2018 - 4:56am
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ICASSP2018-Peng.pdf

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[1] Peng Song, Wenming Zheng, Shifeng Ou,Yun Jin, Wenming Ma, Yanwei Yu, "Joint Transfer Subspace Learning and Feature Selection for Cross-corpus Speech Emotion Recognition", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2980. Accessed: Nov. 19, 2018.
@article{2980-18,
url = {http://sigport.org/2980},
author = {Peng Song, Wenming Zheng, Shifeng Ou,Yun Jin, Wenming Ma, Yanwei Yu },
publisher = {IEEE SigPort},
title = {Joint Transfer Subspace Learning and Feature Selection for Cross-corpus Speech Emotion Recognition},
year = {2018} }
TY - EJOUR
T1 - Joint Transfer Subspace Learning and Feature Selection for Cross-corpus Speech Emotion Recognition
AU - Peng Song, Wenming Zheng, Shifeng Ou,Yun Jin, Wenming Ma, Yanwei Yu
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2980
ER -
Peng Song, Wenming Zheng, Shifeng Ou,Yun Jin, Wenming Ma, Yanwei Yu. (2018). Joint Transfer Subspace Learning and Feature Selection for Cross-corpus Speech Emotion Recognition. IEEE SigPort. http://sigport.org/2980
Peng Song, Wenming Zheng, Shifeng Ou,Yun Jin, Wenming Ma, Yanwei Yu, 2018. Joint Transfer Subspace Learning and Feature Selection for Cross-corpus Speech Emotion Recognition. Available at: http://sigport.org/2980.
Peng Song, Wenming Zheng, Shifeng Ou,Yun Jin, Wenming Ma, Yanwei Yu. (2018). "Joint Transfer Subspace Learning and Feature Selection for Cross-corpus Speech Emotion Recognition." Web.
1. Peng Song, Wenming Zheng, Shifeng Ou,Yun Jin, Wenming Ma, Yanwei Yu. Joint Transfer Subspace Learning and Feature Selection for Cross-corpus Speech Emotion Recognition [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2980

WEIGHTED AND MULTI-TASK LOSS FOR RARE AUDIO EVENT DETECTION

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Authors:
Timo Gerkmann, Alfred Mertins
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17 April 2018 - 3:58pm
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ICASSP2018_Poster.pdf

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[1] Timo Gerkmann, Alfred Mertins, "WEIGHTED AND MULTI-TASK LOSS FOR RARE AUDIO EVENT DETECTION", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2944. Accessed: Nov. 19, 2018.
@article{2944-18,
url = {http://sigport.org/2944},
author = {Timo Gerkmann; Alfred Mertins },
publisher = {IEEE SigPort},
title = {WEIGHTED AND MULTI-TASK LOSS FOR RARE AUDIO EVENT DETECTION},
year = {2018} }
TY - EJOUR
T1 - WEIGHTED AND MULTI-TASK LOSS FOR RARE AUDIO EVENT DETECTION
AU - Timo Gerkmann; Alfred Mertins
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2944
ER -
Timo Gerkmann, Alfred Mertins. (2018). WEIGHTED AND MULTI-TASK LOSS FOR RARE AUDIO EVENT DETECTION. IEEE SigPort. http://sigport.org/2944
Timo Gerkmann, Alfred Mertins, 2018. WEIGHTED AND MULTI-TASK LOSS FOR RARE AUDIO EVENT DETECTION. Available at: http://sigport.org/2944.
Timo Gerkmann, Alfred Mertins. (2018). "WEIGHTED AND MULTI-TASK LOSS FOR RARE AUDIO EVENT DETECTION." Web.
1. Timo Gerkmann, Alfred Mertins. WEIGHTED AND MULTI-TASK LOSS FOR RARE AUDIO EVENT DETECTION [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2944

ENABLING EARLY AUDIO EVENT DETECTION WITH NEURAL NETWORKS

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Authors:
Philipp Koch, Ian McLoughlin, Alfred Mertins
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17 April 2018 - 3:51pm
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icassp2018.pdf

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[1] Philipp Koch, Ian McLoughlin, Alfred Mertins, "ENABLING EARLY AUDIO EVENT DETECTION WITH NEURAL NETWORKS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2943. Accessed: Nov. 19, 2018.
@article{2943-18,
url = {http://sigport.org/2943},
author = {Philipp Koch; Ian McLoughlin; Alfred Mertins },
publisher = {IEEE SigPort},
title = {ENABLING EARLY AUDIO EVENT DETECTION WITH NEURAL NETWORKS},
year = {2018} }
TY - EJOUR
T1 - ENABLING EARLY AUDIO EVENT DETECTION WITH NEURAL NETWORKS
AU - Philipp Koch; Ian McLoughlin; Alfred Mertins
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2943
ER -
Philipp Koch, Ian McLoughlin, Alfred Mertins. (2018). ENABLING EARLY AUDIO EVENT DETECTION WITH NEURAL NETWORKS. IEEE SigPort. http://sigport.org/2943
Philipp Koch, Ian McLoughlin, Alfred Mertins, 2018. ENABLING EARLY AUDIO EVENT DETECTION WITH NEURAL NETWORKS. Available at: http://sigport.org/2943.
Philipp Koch, Ian McLoughlin, Alfred Mertins. (2018). "ENABLING EARLY AUDIO EVENT DETECTION WITH NEURAL NETWORKS." Web.
1. Philipp Koch, Ian McLoughlin, Alfred Mertins. ENABLING EARLY AUDIO EVENT DETECTION WITH NEURAL NETWORKS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2943

Generative Adversarial Source Separation


pres.pdf

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17 April 2018 - 1:03pm
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pres.pdf

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[1] , "Generative Adversarial Source Separation", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2937. Accessed: Nov. 19, 2018.
@article{2937-18,
url = {http://sigport.org/2937},
author = { },
publisher = {IEEE SigPort},
title = {Generative Adversarial Source Separation},
year = {2018} }
TY - EJOUR
T1 - Generative Adversarial Source Separation
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2937
ER -
. (2018). Generative Adversarial Source Separation. IEEE SigPort. http://sigport.org/2937
, 2018. Generative Adversarial Source Separation. Available at: http://sigport.org/2937.
. (2018). "Generative Adversarial Source Separation." Web.
1. . Generative Adversarial Source Separation [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2937

REALIZING DIRECTIONAL SOUND SOURCE IN FDTD METHOD BY ESTIMATING INITIAL VALUE


Wave-based acoustic simulation methods are studied actively for predicting acoustical phenomena. Finite-difference timedomain (FDTD) method is one of the most popular methods owing to its straightforwardness of calculating an impulse response. In an FDTD simulation, an omnidirectional sound source is usually adopted, which is not realistic because the real sound sources often have specific directivities. However, there is very little research on imposing a directional sound source into FDTD methods.

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Authors:
Daiki Takeuchi, Kohei Yatabe, Yasuhiro Oikawa
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17 April 2018 - 10:59am
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ICASSP2018Poster.pdf

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[1] Daiki Takeuchi, Kohei Yatabe, Yasuhiro Oikawa, "REALIZING DIRECTIONAL SOUND SOURCE IN FDTD METHOD BY ESTIMATING INITIAL VALUE", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2936. Accessed: Nov. 19, 2018.
@article{2936-18,
url = {http://sigport.org/2936},
author = {Daiki Takeuchi; Kohei Yatabe; Yasuhiro Oikawa },
publisher = {IEEE SigPort},
title = {REALIZING DIRECTIONAL SOUND SOURCE IN FDTD METHOD BY ESTIMATING INITIAL VALUE},
year = {2018} }
TY - EJOUR
T1 - REALIZING DIRECTIONAL SOUND SOURCE IN FDTD METHOD BY ESTIMATING INITIAL VALUE
AU - Daiki Takeuchi; Kohei Yatabe; Yasuhiro Oikawa
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2936
ER -
Daiki Takeuchi, Kohei Yatabe, Yasuhiro Oikawa. (2018). REALIZING DIRECTIONAL SOUND SOURCE IN FDTD METHOD BY ESTIMATING INITIAL VALUE. IEEE SigPort. http://sigport.org/2936
Daiki Takeuchi, Kohei Yatabe, Yasuhiro Oikawa, 2018. REALIZING DIRECTIONAL SOUND SOURCE IN FDTD METHOD BY ESTIMATING INITIAL VALUE. Available at: http://sigport.org/2936.
Daiki Takeuchi, Kohei Yatabe, Yasuhiro Oikawa. (2018). "REALIZING DIRECTIONAL SOUND SOURCE IN FDTD METHOD BY ESTIMATING INITIAL VALUE." Web.
1. Daiki Takeuchi, Kohei Yatabe, Yasuhiro Oikawa. REALIZING DIRECTIONAL SOUND SOURCE IN FDTD METHOD BY ESTIMATING INITIAL VALUE [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2936

Maximal Figure-of-Merit Embedding for Multi-label Audio Classification

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Authors:
Ivan Kukanov, Ville Hautamaki, Kong Aik Lee
Submitted On:
19 April 2018 - 12:02pm
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Presentation.pdf

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[1] Ivan Kukanov, Ville Hautamaki, Kong Aik Lee, "Maximal Figure-of-Merit Embedding for Multi-label Audio Classification", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2935. Accessed: Nov. 19, 2018.
@article{2935-18,
url = {http://sigport.org/2935},
author = {Ivan Kukanov; Ville Hautamaki; Kong Aik Lee },
publisher = {IEEE SigPort},
title = {Maximal Figure-of-Merit Embedding for Multi-label Audio Classification},
year = {2018} }
TY - EJOUR
T1 - Maximal Figure-of-Merit Embedding for Multi-label Audio Classification
AU - Ivan Kukanov; Ville Hautamaki; Kong Aik Lee
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2935
ER -
Ivan Kukanov, Ville Hautamaki, Kong Aik Lee. (2018). Maximal Figure-of-Merit Embedding for Multi-label Audio Classification. IEEE SigPort. http://sigport.org/2935
Ivan Kukanov, Ville Hautamaki, Kong Aik Lee, 2018. Maximal Figure-of-Merit Embedding for Multi-label Audio Classification. Available at: http://sigport.org/2935.
Ivan Kukanov, Ville Hautamaki, Kong Aik Lee. (2018). "Maximal Figure-of-Merit Embedding for Multi-label Audio Classification." Web.
1. Ivan Kukanov, Ville Hautamaki, Kong Aik Lee. Maximal Figure-of-Merit Embedding for Multi-label Audio Classification [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2935

Time-Frequency Networks for Audio Super-Resolution


Audio super-resolution (a.k.a. bandwidth extension) is the challenging task of increasing the temporal resolution of audio signals. Recent deep networks approaches achieved promising results by modeling the task as a regression problem in either time or frequency domain. In this paper, we introduced Time-Frequency Network (TFNet), a deep network that utilizes supervision in both the time and frequency domain. We proposed a novel model architecture which allows the two domains to be jointly optimized.

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Authors:
Yijia Xu, Minh N. Do, Mark Hasegawa-Johnson
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17 April 2018 - 12:54am
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audio_sr_poster.pdf

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[1] Yijia Xu, Minh N. Do, Mark Hasegawa-Johnson, "Time-Frequency Networks for Audio Super-Resolution", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2928. Accessed: Nov. 19, 2018.
@article{2928-18,
url = {http://sigport.org/2928},
author = {Yijia Xu; Minh N. Do; Mark Hasegawa-Johnson },
publisher = {IEEE SigPort},
title = {Time-Frequency Networks for Audio Super-Resolution},
year = {2018} }
TY - EJOUR
T1 - Time-Frequency Networks for Audio Super-Resolution
AU - Yijia Xu; Minh N. Do; Mark Hasegawa-Johnson
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2928
ER -
Yijia Xu, Minh N. Do, Mark Hasegawa-Johnson. (2018). Time-Frequency Networks for Audio Super-Resolution. IEEE SigPort. http://sigport.org/2928
Yijia Xu, Minh N. Do, Mark Hasegawa-Johnson, 2018. Time-Frequency Networks for Audio Super-Resolution. Available at: http://sigport.org/2928.
Yijia Xu, Minh N. Do, Mark Hasegawa-Johnson. (2018). "Time-Frequency Networks for Audio Super-Resolution." Web.
1. Yijia Xu, Minh N. Do, Mark Hasegawa-Johnson. Time-Frequency Networks for Audio Super-Resolution [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2928

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