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ICASSP 2020

ICASSP is the world’s largest and most comprehensive technical conference focused on signal processing and its applications. The ICASSP 2020 conference will feature world-class presentations by internationally renowned speakers, cutting-edge session topics and provide a fantastic opportunity to network with like-minded professionals from around the world. Visit website.

Time Difference of Arrival Estimation from Frequency-sliding Generalized Cross-Correlations Using Convolutional Neural Networks​


The interest in deep learning methods for solving traditional signal processing tasks has been steadily growing in the last years.

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Authors:
Luca Comanducci, Maximo Cobos, Fabio Antonacci, Augusto Sarti
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20 May 2020 - 3:02pm
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[1] Luca Comanducci, Maximo Cobos, Fabio Antonacci, Augusto Sarti, "Time Difference of Arrival Estimation from Frequency-sliding Generalized Cross-Correlations Using Convolutional Neural Networks​", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5419. Accessed: Aug. 05, 2020.
@article{5419-20,
url = {http://sigport.org/5419},
author = {Luca Comanducci; Maximo Cobos; Fabio Antonacci; Augusto Sarti },
publisher = {IEEE SigPort},
title = {Time Difference of Arrival Estimation from Frequency-sliding Generalized Cross-Correlations Using Convolutional Neural Networks​},
year = {2020} }
TY - EJOUR
T1 - Time Difference of Arrival Estimation from Frequency-sliding Generalized Cross-Correlations Using Convolutional Neural Networks​
AU - Luca Comanducci; Maximo Cobos; Fabio Antonacci; Augusto Sarti
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5419
ER -
Luca Comanducci, Maximo Cobos, Fabio Antonacci, Augusto Sarti. (2020). Time Difference of Arrival Estimation from Frequency-sliding Generalized Cross-Correlations Using Convolutional Neural Networks​. IEEE SigPort. http://sigport.org/5419
Luca Comanducci, Maximo Cobos, Fabio Antonacci, Augusto Sarti, 2020. Time Difference of Arrival Estimation from Frequency-sliding Generalized Cross-Correlations Using Convolutional Neural Networks​. Available at: http://sigport.org/5419.
Luca Comanducci, Maximo Cobos, Fabio Antonacci, Augusto Sarti. (2020). "Time Difference of Arrival Estimation from Frequency-sliding Generalized Cross-Correlations Using Convolutional Neural Networks​." Web.
1. Luca Comanducci, Maximo Cobos, Fabio Antonacci, Augusto Sarti. Time Difference of Arrival Estimation from Frequency-sliding Generalized Cross-Correlations Using Convolutional Neural Networks​ [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5419

MULTI IMAGE DEPTH FROM DEFOCUS NETWORK WITH BOUNDARY CUE FOR DUAL APERTURE CAMERA


In this paper, we estimate depth information using two defocused images from dual aperture camera. Recent advances in deep learning techniques have increased the accuracy of depth estimation. Besides, methods of using a defocused image in which an object is blurred according to a distance from a camera have been widely studied. We further improve the accuracy of the depth estimation by training the network using two images with different degrees of depth-of-field.

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Authors:
Gwangmo Song, Yumee Kim, Kukjin Chun, Kyoung Mu Lee
Submitted On:
20 May 2020 - 11:55am
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[1] Gwangmo Song, Yumee Kim, Kukjin Chun, Kyoung Mu Lee, "MULTI IMAGE DEPTH FROM DEFOCUS NETWORK WITH BOUNDARY CUE FOR DUAL APERTURE CAMERA", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5418. Accessed: Aug. 05, 2020.
@article{5418-20,
url = {http://sigport.org/5418},
author = {Gwangmo Song; Yumee Kim; Kukjin Chun; Kyoung Mu Lee },
publisher = {IEEE SigPort},
title = {MULTI IMAGE DEPTH FROM DEFOCUS NETWORK WITH BOUNDARY CUE FOR DUAL APERTURE CAMERA},
year = {2020} }
TY - EJOUR
T1 - MULTI IMAGE DEPTH FROM DEFOCUS NETWORK WITH BOUNDARY CUE FOR DUAL APERTURE CAMERA
AU - Gwangmo Song; Yumee Kim; Kukjin Chun; Kyoung Mu Lee
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5418
ER -
Gwangmo Song, Yumee Kim, Kukjin Chun, Kyoung Mu Lee. (2020). MULTI IMAGE DEPTH FROM DEFOCUS NETWORK WITH BOUNDARY CUE FOR DUAL APERTURE CAMERA. IEEE SigPort. http://sigport.org/5418
Gwangmo Song, Yumee Kim, Kukjin Chun, Kyoung Mu Lee, 2020. MULTI IMAGE DEPTH FROM DEFOCUS NETWORK WITH BOUNDARY CUE FOR DUAL APERTURE CAMERA. Available at: http://sigport.org/5418.
Gwangmo Song, Yumee Kim, Kukjin Chun, Kyoung Mu Lee. (2020). "MULTI IMAGE DEPTH FROM DEFOCUS NETWORK WITH BOUNDARY CUE FOR DUAL APERTURE CAMERA." Web.
1. Gwangmo Song, Yumee Kim, Kukjin Chun, Kyoung Mu Lee. MULTI IMAGE DEPTH FROM DEFOCUS NETWORK WITH BOUNDARY CUE FOR DUAL APERTURE CAMERA [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5418

EMET : EMBEDDINGS FROM MULTILINGUAL- ENCODER TRANSFORMER FOR FAKE NEWS DETECTION


In the last few years, social media networks have changed human life experience and behavior as it has broken down communication barriers, allowing ordinary people to actively produce multimedia content on a massive scale. On this wise, the information dissemination in social media platforms becomes increasingly common. However, misinformation is propagated with the same facility and velocity as real news, though it can result in irreversible damage to an individual or society at large.

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Authors:
Stephane Schwarz ; Antônio Theóphilo ; Anderson Rocha
Submitted On:
20 May 2020 - 11:36am
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[1] Stephane Schwarz ; Antônio Theóphilo ; Anderson Rocha , "EMET : EMBEDDINGS FROM MULTILINGUAL- ENCODER TRANSFORMER FOR FAKE NEWS DETECTION", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5417. Accessed: Aug. 05, 2020.
@article{5417-20,
url = {http://sigport.org/5417},
author = {Stephane Schwarz ; Antônio Theóphilo ; Anderson Rocha },
publisher = {IEEE SigPort},
title = {EMET : EMBEDDINGS FROM MULTILINGUAL- ENCODER TRANSFORMER FOR FAKE NEWS DETECTION},
year = {2020} }
TY - EJOUR
T1 - EMET : EMBEDDINGS FROM MULTILINGUAL- ENCODER TRANSFORMER FOR FAKE NEWS DETECTION
AU - Stephane Schwarz ; Antônio Theóphilo ; Anderson Rocha
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5417
ER -
Stephane Schwarz ; Antônio Theóphilo ; Anderson Rocha . (2020). EMET : EMBEDDINGS FROM MULTILINGUAL- ENCODER TRANSFORMER FOR FAKE NEWS DETECTION. IEEE SigPort. http://sigport.org/5417
Stephane Schwarz ; Antônio Theóphilo ; Anderson Rocha , 2020. EMET : EMBEDDINGS FROM MULTILINGUAL- ENCODER TRANSFORMER FOR FAKE NEWS DETECTION. Available at: http://sigport.org/5417.
Stephane Schwarz ; Antônio Theóphilo ; Anderson Rocha . (2020). "EMET : EMBEDDINGS FROM MULTILINGUAL- ENCODER TRANSFORMER FOR FAKE NEWS DETECTION." Web.
1. Stephane Schwarz ; Antônio Theóphilo ; Anderson Rocha . EMET : EMBEDDINGS FROM MULTILINGUAL- ENCODER TRANSFORMER FOR FAKE NEWS DETECTION [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5417

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: Aug. 05, 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

Curriculum learning for speech emotion recognition from crowdsourced labels


This study introduces a method to design a curriculum for machine-learning to maximize the efficiency during the training process of deep neural networks (DNNs) for speech emotion recognition. Previous studies in other machine-learning problems have shown the benefits of training a classifier following a curriculum where samples are gradually presented in increasing level of difficulty. For speech emotion recognition, the challenge is to establish a natural order of difficulty in the training set to create the curriculum.

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Authors:
Reza Lotfian, Carlos Busso
Submitted On:
20 May 2020 - 9:43am
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[1] Reza Lotfian, Carlos Busso, "Curriculum learning for speech emotion recognition from crowdsourced labels", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5408. Accessed: Aug. 05, 2020.
@article{5408-20,
url = {http://sigport.org/5408},
author = {Reza Lotfian; Carlos Busso },
publisher = {IEEE SigPort},
title = {Curriculum learning for speech emotion recognition from crowdsourced labels},
year = {2020} }
TY - EJOUR
T1 - Curriculum learning for speech emotion recognition from crowdsourced labels
AU - Reza Lotfian; Carlos Busso
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5408
ER -
Reza Lotfian, Carlos Busso. (2020). Curriculum learning for speech emotion recognition from crowdsourced labels. IEEE SigPort. http://sigport.org/5408
Reza Lotfian, Carlos Busso, 2020. Curriculum learning for speech emotion recognition from crowdsourced labels. Available at: http://sigport.org/5408.
Reza Lotfian, Carlos Busso. (2020). "Curriculum learning for speech emotion recognition from crowdsourced labels." Web.
1. Reza Lotfian, Carlos Busso. Curriculum learning for speech emotion recognition from crowdsourced labels [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5408

DNN-BASED SPEECH RECOGNITION FOR GLOBALPHONE LANGUAGES


This paper describes new reference benchmark results based on hybrid Hidden Markov Model and Deep Neural Networks (HMM-DNN) for the GlobalPhone (GP) multilingual text and speech database. GP is a multilingual database of high-quality read speech with corresponding transcriptions and pronunciation dictionaries in more than 20 languages. Moreover, we provide new results for five additional languages, namely, Amharic, Oromo, Tigrigna, Wolaytta, and Uyghur.

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Authors:
Martha Yifiru Tachbelie, Ayimunishagu Abulimiti, Solomon Teferra Abate, Tanja Schultz
Submitted On:
20 May 2020 - 9:12am
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[1] Martha Yifiru Tachbelie, Ayimunishagu Abulimiti, Solomon Teferra Abate, Tanja Schultz, "DNN-BASED SPEECH RECOGNITION FOR GLOBALPHONE LANGUAGES", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5407. Accessed: Aug. 05, 2020.
@article{5407-20,
url = {http://sigport.org/5407},
author = {Martha Yifiru Tachbelie; Ayimunishagu Abulimiti; Solomon Teferra Abate; Tanja Schultz },
publisher = {IEEE SigPort},
title = {DNN-BASED SPEECH RECOGNITION FOR GLOBALPHONE LANGUAGES},
year = {2020} }
TY - EJOUR
T1 - DNN-BASED SPEECH RECOGNITION FOR GLOBALPHONE LANGUAGES
AU - Martha Yifiru Tachbelie; Ayimunishagu Abulimiti; Solomon Teferra Abate; Tanja Schultz
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5407
ER -
Martha Yifiru Tachbelie, Ayimunishagu Abulimiti, Solomon Teferra Abate, Tanja Schultz. (2020). DNN-BASED SPEECH RECOGNITION FOR GLOBALPHONE LANGUAGES. IEEE SigPort. http://sigport.org/5407
Martha Yifiru Tachbelie, Ayimunishagu Abulimiti, Solomon Teferra Abate, Tanja Schultz, 2020. DNN-BASED SPEECH RECOGNITION FOR GLOBALPHONE LANGUAGES. Available at: http://sigport.org/5407.
Martha Yifiru Tachbelie, Ayimunishagu Abulimiti, Solomon Teferra Abate, Tanja Schultz. (2020). "DNN-BASED SPEECH RECOGNITION FOR GLOBALPHONE LANGUAGES." Web.
1. Martha Yifiru Tachbelie, Ayimunishagu Abulimiti, Solomon Teferra Abate, Tanja Schultz. DNN-BASED SPEECH RECOGNITION FOR GLOBALPHONE LANGUAGES [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5407

Semi-Supervised Optimal Transport Methods for Detecting Anomalies


Building upon advances on optimal transport and anomaly detection, we propose a generalization of an unsupervised and automatic method for detection of significant deviation from reference signals. Unlike most existing approaches for anomaly detection, our method is built on a non-parametric framework exploiting the optimal transportation to estimate deviation from an observed distribution.

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Authors:
Amina Alaoui-Belghiti, Sylvain Chevallier, Eric Monacelli, Guillaume Bao, Eric Azabou
Submitted On:
20 May 2020 - 8:36am
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[1] Amina Alaoui-Belghiti, Sylvain Chevallier, Eric Monacelli, Guillaume Bao, Eric Azabou, "Semi-Supervised Optimal Transport Methods for Detecting Anomalies", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5406. Accessed: Aug. 05, 2020.
@article{5406-20,
url = {http://sigport.org/5406},
author = { Amina Alaoui-Belghiti; Sylvain Chevallier; Eric Monacelli; Guillaume Bao; Eric Azabou },
publisher = {IEEE SigPort},
title = {Semi-Supervised Optimal Transport Methods for Detecting Anomalies},
year = {2020} }
TY - EJOUR
T1 - Semi-Supervised Optimal Transport Methods for Detecting Anomalies
AU - Amina Alaoui-Belghiti; Sylvain Chevallier; Eric Monacelli; Guillaume Bao; Eric Azabou
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5406
ER -
Amina Alaoui-Belghiti, Sylvain Chevallier, Eric Monacelli, Guillaume Bao, Eric Azabou. (2020). Semi-Supervised Optimal Transport Methods for Detecting Anomalies. IEEE SigPort. http://sigport.org/5406
Amina Alaoui-Belghiti, Sylvain Chevallier, Eric Monacelli, Guillaume Bao, Eric Azabou, 2020. Semi-Supervised Optimal Transport Methods for Detecting Anomalies. Available at: http://sigport.org/5406.
Amina Alaoui-Belghiti, Sylvain Chevallier, Eric Monacelli, Guillaume Bao, Eric Azabou. (2020). "Semi-Supervised Optimal Transport Methods for Detecting Anomalies." Web.
1. Amina Alaoui-Belghiti, Sylvain Chevallier, Eric Monacelli, Guillaume Bao, Eric Azabou. Semi-Supervised Optimal Transport Methods for Detecting Anomalies [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5406

Recovery of binary sparse signals from compressed linear measurements via polynomial optimization

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20 May 2020 - 5:38am
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[1] , "Recovery of binary sparse signals from compressed linear measurements via polynomial optimization", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5405. Accessed: Aug. 05, 2020.
@article{5405-20,
url = {http://sigport.org/5405},
author = { },
publisher = {IEEE SigPort},
title = {Recovery of binary sparse signals from compressed linear measurements via polynomial optimization},
year = {2020} }
TY - EJOUR
T1 - Recovery of binary sparse signals from compressed linear measurements via polynomial optimization
AU -
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5405
ER -
. (2020). Recovery of binary sparse signals from compressed linear measurements via polynomial optimization. IEEE SigPort. http://sigport.org/5405
, 2020. Recovery of binary sparse signals from compressed linear measurements via polynomial optimization. Available at: http://sigport.org/5405.
. (2020). "Recovery of binary sparse signals from compressed linear measurements via polynomial optimization." Web.
1. . Recovery of binary sparse signals from compressed linear measurements via polynomial optimization [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5405

DEEP ENCODED LINGUISTIC AND ACOUSTIC CUES FOR ATTENTION BASED END TO END SPEECH EMOTION RECOGNITION

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Authors:
Swapnil Bhosale, Rupayan Chakraborty, Sunil Kumar Kopparapu
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20 May 2020 - 5:22am
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[1] Swapnil Bhosale, Rupayan Chakraborty, Sunil Kumar Kopparapu, "DEEP ENCODED LINGUISTIC AND ACOUSTIC CUES FOR ATTENTION BASED END TO END SPEECH EMOTION RECOGNITION", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5404. Accessed: Aug. 05, 2020.
@article{5404-20,
url = {http://sigport.org/5404},
author = {Swapnil Bhosale; Rupayan Chakraborty; Sunil Kumar Kopparapu },
publisher = {IEEE SigPort},
title = {DEEP ENCODED LINGUISTIC AND ACOUSTIC CUES FOR ATTENTION BASED END TO END SPEECH EMOTION RECOGNITION},
year = {2020} }
TY - EJOUR
T1 - DEEP ENCODED LINGUISTIC AND ACOUSTIC CUES FOR ATTENTION BASED END TO END SPEECH EMOTION RECOGNITION
AU - Swapnil Bhosale; Rupayan Chakraborty; Sunil Kumar Kopparapu
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5404
ER -
Swapnil Bhosale, Rupayan Chakraborty, Sunil Kumar Kopparapu. (2020). DEEP ENCODED LINGUISTIC AND ACOUSTIC CUES FOR ATTENTION BASED END TO END SPEECH EMOTION RECOGNITION. IEEE SigPort. http://sigport.org/5404
Swapnil Bhosale, Rupayan Chakraborty, Sunil Kumar Kopparapu, 2020. DEEP ENCODED LINGUISTIC AND ACOUSTIC CUES FOR ATTENTION BASED END TO END SPEECH EMOTION RECOGNITION. Available at: http://sigport.org/5404.
Swapnil Bhosale, Rupayan Chakraborty, Sunil Kumar Kopparapu. (2020). "DEEP ENCODED LINGUISTIC AND ACOUSTIC CUES FOR ATTENTION BASED END TO END SPEECH EMOTION RECOGNITION." Web.
1. Swapnil Bhosale, Rupayan Chakraborty, Sunil Kumar Kopparapu. DEEP ENCODED LINGUISTIC AND ACOUSTIC CUES FOR ATTENTION BASED END TO END SPEECH EMOTION RECOGNITION [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5404

Multi-Conditioning & Data Augmentation using Generative Noise Model for Speech Emotion Recognition in Noisy Conditions


Degradation due to additive noise is a significant road block in the real-life deployment of Speech Emotion Recognition (SER) systems. Most of the previous work in this field dealt with the noise degradation either at the signal or at the feature level. In this paper, to address the robustness aspect of the SER in additive noise scenarios, we propose multi-conditioning and data augmentation using an utterance level parametric generative noise model. The generative noise model is designed to generate noise types which can span the entire noise space in the mel-filterbank energy domain.

Paper Details

Authors:
Upasana Tiwari, Meet Soni, Rupayan Chakraborty, Ashish Panda, Sunil Kumar Kopparapu
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20 May 2020 - 5:01am
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[1] Upasana Tiwari, Meet Soni, Rupayan Chakraborty, Ashish Panda, Sunil Kumar Kopparapu, "Multi-Conditioning & Data Augmentation using Generative Noise Model for Speech Emotion Recognition in Noisy Conditions", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5403. Accessed: Aug. 05, 2020.
@article{5403-20,
url = {http://sigport.org/5403},
author = {Upasana Tiwari; Meet Soni; Rupayan Chakraborty; Ashish Panda; Sunil Kumar Kopparapu },
publisher = {IEEE SigPort},
title = {Multi-Conditioning & Data Augmentation using Generative Noise Model for Speech Emotion Recognition in Noisy Conditions},
year = {2020} }
TY - EJOUR
T1 - Multi-Conditioning & Data Augmentation using Generative Noise Model for Speech Emotion Recognition in Noisy Conditions
AU - Upasana Tiwari; Meet Soni; Rupayan Chakraborty; Ashish Panda; Sunil Kumar Kopparapu
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5403
ER -
Upasana Tiwari, Meet Soni, Rupayan Chakraborty, Ashish Panda, Sunil Kumar Kopparapu. (2020). Multi-Conditioning & Data Augmentation using Generative Noise Model for Speech Emotion Recognition in Noisy Conditions. IEEE SigPort. http://sigport.org/5403
Upasana Tiwari, Meet Soni, Rupayan Chakraborty, Ashish Panda, Sunil Kumar Kopparapu, 2020. Multi-Conditioning & Data Augmentation using Generative Noise Model for Speech Emotion Recognition in Noisy Conditions. Available at: http://sigport.org/5403.
Upasana Tiwari, Meet Soni, Rupayan Chakraborty, Ashish Panda, Sunil Kumar Kopparapu. (2020). "Multi-Conditioning & Data Augmentation using Generative Noise Model for Speech Emotion Recognition in Noisy Conditions." Web.
1. Upasana Tiwari, Meet Soni, Rupayan Chakraborty, Ashish Panda, Sunil Kumar Kopparapu. Multi-Conditioning & Data Augmentation using Generative Noise Model for Speech Emotion Recognition in Noisy Conditions [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5403

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