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Room Acoustics and Acoustic System Modeling

Blind Room Volume Estimation from Single-Channel Noisy Speech


Recent work on acoustic parameter estimation indicates that geometric room volume can be useful for modeling the character of an acoustic environment. However, estimating volume from audio signals remains a challenging problem. Here we propose using a convolutional neural network model to estimate the room volume blindly from reverberant single-channel speech signals in the presence of noise. The model is shown to produce estimates within approximately a factor of two to the true value, for rooms ranging in size from small offices to large concert halls.

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Authors:
Andrea Genovese, Hannes Gamper, Ville Pullki, Nikunj Raghuvanshi, Ivan Tashev
Submitted On:
10 May 2019 - 2:44am
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[1] Andrea Genovese, Hannes Gamper, Ville Pullki, Nikunj Raghuvanshi, Ivan Tashev, "Blind Room Volume Estimation from Single-Channel Noisy Speech", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4277. Accessed: Jun. 26, 2019.
@article{4277-19,
url = {http://sigport.org/4277},
author = {Andrea Genovese; Hannes Gamper; Ville Pullki; Nikunj Raghuvanshi; Ivan Tashev },
publisher = {IEEE SigPort},
title = {Blind Room Volume Estimation from Single-Channel Noisy Speech},
year = {2019} }
TY - EJOUR
T1 - Blind Room Volume Estimation from Single-Channel Noisy Speech
AU - Andrea Genovese; Hannes Gamper; Ville Pullki; Nikunj Raghuvanshi; Ivan Tashev
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4277
ER -
Andrea Genovese, Hannes Gamper, Ville Pullki, Nikunj Raghuvanshi, Ivan Tashev. (2019). Blind Room Volume Estimation from Single-Channel Noisy Speech. IEEE SigPort. http://sigport.org/4277
Andrea Genovese, Hannes Gamper, Ville Pullki, Nikunj Raghuvanshi, Ivan Tashev, 2019. Blind Room Volume Estimation from Single-Channel Noisy Speech. Available at: http://sigport.org/4277.
Andrea Genovese, Hannes Gamper, Ville Pullki, Nikunj Raghuvanshi, Ivan Tashev. (2019). "Blind Room Volume Estimation from Single-Channel Noisy Speech." Web.
1. Andrea Genovese, Hannes Gamper, Ville Pullki, Nikunj Raghuvanshi, Ivan Tashev. Blind Room Volume Estimation from Single-Channel Noisy Speech [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4277

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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[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. 26, 2019.
@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

SOUND SOURCE LOCALIZATION IN A REVERBERANT ROOM USING HARMONIC BASED MUSIC


The localization of acoustic sound sources is beneficial to signal processing applications of speech enhancement, dereverberation, separation and tracking. Difficulties in position estimation arise in real world environments due to coherent reflections degrading performance of subspace localization techniques. This paper proposes a method of multiple signal classification (MUSIC) subspace localization, which is suitable for reverberant rooms. The method is based on the modal decomposition of a room's region-to-region transfer function, which is assumed to be known.

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Authors:
Lachlan Birnie, Thushara Abhayapala, Hanchi Chen, Prasanga Samarasinghe
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7 May 2019 - 8:15pm
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[1] Lachlan Birnie, Thushara Abhayapala, Hanchi Chen, Prasanga Samarasinghe, "SOUND SOURCE LOCALIZATION IN A REVERBERANT ROOM USING HARMONIC BASED MUSIC", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3972. Accessed: Jun. 26, 2019.
@article{3972-19,
url = {http://sigport.org/3972},
author = {Lachlan Birnie; Thushara Abhayapala; Hanchi Chen; Prasanga Samarasinghe },
publisher = {IEEE SigPort},
title = {SOUND SOURCE LOCALIZATION IN A REVERBERANT ROOM USING HARMONIC BASED MUSIC},
year = {2019} }
TY - EJOUR
T1 - SOUND SOURCE LOCALIZATION IN A REVERBERANT ROOM USING HARMONIC BASED MUSIC
AU - Lachlan Birnie; Thushara Abhayapala; Hanchi Chen; Prasanga Samarasinghe
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3972
ER -
Lachlan Birnie, Thushara Abhayapala, Hanchi Chen, Prasanga Samarasinghe. (2019). SOUND SOURCE LOCALIZATION IN A REVERBERANT ROOM USING HARMONIC BASED MUSIC. IEEE SigPort. http://sigport.org/3972
Lachlan Birnie, Thushara Abhayapala, Hanchi Chen, Prasanga Samarasinghe, 2019. SOUND SOURCE LOCALIZATION IN A REVERBERANT ROOM USING HARMONIC BASED MUSIC. Available at: http://sigport.org/3972.
Lachlan Birnie, Thushara Abhayapala, Hanchi Chen, Prasanga Samarasinghe. (2019). "SOUND SOURCE LOCALIZATION IN A REVERBERANT ROOM USING HARMONIC BASED MUSIC." Web.
1. Lachlan Birnie, Thushara Abhayapala, Hanchi Chen, Prasanga Samarasinghe. SOUND SOURCE LOCALIZATION IN A REVERBERANT ROOM USING HARMONIC BASED MUSIC [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3972

Joint Estimation of the Room Geometry and Modes with Compressed Sensing


Acoustical behavior of a room for a given position of microphone and sound source is usually described using the room impulse response. If we rely on the standard uniform sampling, the estimation of room impulse response for arbitrary positions in the room requires a large number of measurements. In order to lower the required sampling rate, some solutions have emerged that exploit the sparse representation of the room wavefield in the terms of plane waves in the low-frequency domain. The plane wave representation has a simple form in rectangular rooms.

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13 April 2018 - 10:07am
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[1] , "Joint Estimation of the Room Geometry and Modes with Compressed Sensing", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2708. Accessed: Jun. 26, 2019.
@article{2708-18,
url = {http://sigport.org/2708},
author = { },
publisher = {IEEE SigPort},
title = {Joint Estimation of the Room Geometry and Modes with Compressed Sensing},
year = {2018} }
TY - EJOUR
T1 - Joint Estimation of the Room Geometry and Modes with Compressed Sensing
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2708
ER -
. (2018). Joint Estimation of the Room Geometry and Modes with Compressed Sensing. IEEE SigPort. http://sigport.org/2708
, 2018. Joint Estimation of the Room Geometry and Modes with Compressed Sensing. Available at: http://sigport.org/2708.
. (2018). "Joint Estimation of the Room Geometry and Modes with Compressed Sensing." Web.
1. . Joint Estimation of the Room Geometry and Modes with Compressed Sensing [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2708

ROBUST SEQUENCE-BASED LOCALIZATION IN ACOUSTIC SENSOR NETWORKS


Acoustic source localization in sensor network is a challenging task because of severe constraints on cost, energy, and effective range of sensor devices. To overcome these limitations in existing solutions, this paper formally describes, designs, implements, and evaluates a Half Plane Intersection method to Sequence-Based Localization, i.e., HPI-SBL, in distributed smartphone networks. The localization space can be divided into distinct regions, and each region can be uniquely identified by the node sequence that represents the ranking of distances from the reference nodes to the region.

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Authors:
Naigao Jin, Xin Zhou, Zihan Wang, Yu Liu, Lei Wang
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13 April 2018 - 2:01am
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[1] Naigao Jin, Xin Zhou, Zihan Wang, Yu Liu, Lei Wang, "ROBUST SEQUENCE-BASED LOCALIZATION IN ACOUSTIC SENSOR NETWORKS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2616. Accessed: Jun. 26, 2019.
@article{2616-18,
url = {http://sigport.org/2616},
author = {Naigao Jin; Xin Zhou; Zihan Wang; Yu Liu; Lei Wang },
publisher = {IEEE SigPort},
title = {ROBUST SEQUENCE-BASED LOCALIZATION IN ACOUSTIC SENSOR NETWORKS},
year = {2018} }
TY - EJOUR
T1 - ROBUST SEQUENCE-BASED LOCALIZATION IN ACOUSTIC SENSOR NETWORKS
AU - Naigao Jin; Xin Zhou; Zihan Wang; Yu Liu; Lei Wang
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2616
ER -
Naigao Jin, Xin Zhou, Zihan Wang, Yu Liu, Lei Wang. (2018). ROBUST SEQUENCE-BASED LOCALIZATION IN ACOUSTIC SENSOR NETWORKS. IEEE SigPort. http://sigport.org/2616
Naigao Jin, Xin Zhou, Zihan Wang, Yu Liu, Lei Wang, 2018. ROBUST SEQUENCE-BASED LOCALIZATION IN ACOUSTIC SENSOR NETWORKS. Available at: http://sigport.org/2616.
Naigao Jin, Xin Zhou, Zihan Wang, Yu Liu, Lei Wang. (2018). "ROBUST SEQUENCE-BASED LOCALIZATION IN ACOUSTIC SENSOR NETWORKS." Web.
1. Naigao Jin, Xin Zhou, Zihan Wang, Yu Liu, Lei Wang. ROBUST SEQUENCE-BASED LOCALIZATION IN ACOUSTIC SENSOR NETWORKS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2616

ESTIMATION OF TIME-VARYING ROOM IMPULSE RESPONSES OF MULTIPLE SOUND SOURCES FROM OBSERVED MIXTURE AND ISOLATED SOURCE SIGNALS

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Authors:
Joonas Nikunen, Tuomas Virtanen
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13 April 2018 - 1:31am
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[1] Joonas Nikunen, Tuomas Virtanen, "ESTIMATION OF TIME-VARYING ROOM IMPULSE RESPONSES OF MULTIPLE SOUND SOURCES FROM OBSERVED MIXTURE AND ISOLATED SOURCE SIGNALS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2609. Accessed: Jun. 26, 2019.
@article{2609-18,
url = {http://sigport.org/2609},
author = {Joonas Nikunen; Tuomas Virtanen },
publisher = {IEEE SigPort},
title = {ESTIMATION OF TIME-VARYING ROOM IMPULSE RESPONSES OF MULTIPLE SOUND SOURCES FROM OBSERVED MIXTURE AND ISOLATED SOURCE SIGNALS},
year = {2018} }
TY - EJOUR
T1 - ESTIMATION OF TIME-VARYING ROOM IMPULSE RESPONSES OF MULTIPLE SOUND SOURCES FROM OBSERVED MIXTURE AND ISOLATED SOURCE SIGNALS
AU - Joonas Nikunen; Tuomas Virtanen
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2609
ER -
Joonas Nikunen, Tuomas Virtanen. (2018). ESTIMATION OF TIME-VARYING ROOM IMPULSE RESPONSES OF MULTIPLE SOUND SOURCES FROM OBSERVED MIXTURE AND ISOLATED SOURCE SIGNALS. IEEE SigPort. http://sigport.org/2609
Joonas Nikunen, Tuomas Virtanen, 2018. ESTIMATION OF TIME-VARYING ROOM IMPULSE RESPONSES OF MULTIPLE SOUND SOURCES FROM OBSERVED MIXTURE AND ISOLATED SOURCE SIGNALS. Available at: http://sigport.org/2609.
Joonas Nikunen, Tuomas Virtanen. (2018). "ESTIMATION OF TIME-VARYING ROOM IMPULSE RESPONSES OF MULTIPLE SOUND SOURCES FROM OBSERVED MIXTURE AND ISOLATED SOURCE SIGNALS." Web.
1. Joonas Nikunen, Tuomas Virtanen. ESTIMATION OF TIME-VARYING ROOM IMPULSE RESPONSES OF MULTIPLE SOUND SOURCES FROM OBSERVED MIXTURE AND ISOLATED SOURCE SIGNALS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2609

Speech Dereverberation Based on Integrated Deep and Ensemble Learning Algorithm

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Authors:
Wei-Jen Lee, Fei Chen, Xugang Lu, Shao-Yi Chien,Yu Tsao
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12 April 2018 - 10:44pm
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[1] Wei-Jen Lee, Fei Chen, Xugang Lu, Shao-Yi Chien,Yu Tsao, "Speech Dereverberation Based on Integrated Deep and Ensemble Learning Algorithm", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2563. Accessed: Jun. 26, 2019.
@article{2563-18,
url = {http://sigport.org/2563},
author = {Wei-Jen Lee; Fei Chen; Xugang Lu; Shao-Yi Chien;Yu Tsao },
publisher = {IEEE SigPort},
title = {Speech Dereverberation Based on Integrated Deep and Ensemble Learning Algorithm},
year = {2018} }
TY - EJOUR
T1 - Speech Dereverberation Based on Integrated Deep and Ensemble Learning Algorithm
AU - Wei-Jen Lee; Fei Chen; Xugang Lu; Shao-Yi Chien;Yu Tsao
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2563
ER -
Wei-Jen Lee, Fei Chen, Xugang Lu, Shao-Yi Chien,Yu Tsao. (2018). Speech Dereverberation Based on Integrated Deep and Ensemble Learning Algorithm. IEEE SigPort. http://sigport.org/2563
Wei-Jen Lee, Fei Chen, Xugang Lu, Shao-Yi Chien,Yu Tsao, 2018. Speech Dereverberation Based on Integrated Deep and Ensemble Learning Algorithm. Available at: http://sigport.org/2563.
Wei-Jen Lee, Fei Chen, Xugang Lu, Shao-Yi Chien,Yu Tsao. (2018). "Speech Dereverberation Based on Integrated Deep and Ensemble Learning Algorithm." Web.
1. Wei-Jen Lee, Fei Chen, Xugang Lu, Shao-Yi Chien,Yu Tsao. Speech Dereverberation Based on Integrated Deep and Ensemble Learning Algorithm [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2563

Improved Noise Characterization for Relative Impulse Response Estimation


Relative Impulse Responses (ReIRs) have several applications in speech enhancement, noise suppression and source localization for multi-channel speech processing in reverberant environments. Noise is usually assumed to be white Gaussian during the estimation of the ReIR between two microphones. We show that the noise in this system identification problem is instead dependent upon the microphone measurements and the ReIR itself.

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Authors:
Bhaskar D. Rao, Ritwik Giri, Tao Zhang
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12 April 2018 - 4:38pm
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[1] Bhaskar D. Rao, Ritwik Giri, Tao Zhang, "Improved Noise Characterization for Relative Impulse Response Estimation", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2497. Accessed: Jun. 26, 2019.
@article{2497-18,
url = {http://sigport.org/2497},
author = {Bhaskar D. Rao; Ritwik Giri; Tao Zhang },
publisher = {IEEE SigPort},
title = {Improved Noise Characterization for Relative Impulse Response Estimation},
year = {2018} }
TY - EJOUR
T1 - Improved Noise Characterization for Relative Impulse Response Estimation
AU - Bhaskar D. Rao; Ritwik Giri; Tao Zhang
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2497
ER -
Bhaskar D. Rao, Ritwik Giri, Tao Zhang. (2018). Improved Noise Characterization for Relative Impulse Response Estimation. IEEE SigPort. http://sigport.org/2497
Bhaskar D. Rao, Ritwik Giri, Tao Zhang, 2018. Improved Noise Characterization for Relative Impulse Response Estimation. Available at: http://sigport.org/2497.
Bhaskar D. Rao, Ritwik Giri, Tao Zhang. (2018). "Improved Noise Characterization for Relative Impulse Response Estimation." Web.
1. Bhaskar D. Rao, Ritwik Giri, Tao Zhang. Improved Noise Characterization for Relative Impulse Response Estimation [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2497

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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[1] Kenji Aono, Shantanu Chakrabartty, Toshihiko Yamasaki, "INFRASONIC SCENE FINGERPRINTING FOR AUTHENTICATING SPEAKER LOCATION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1766. Accessed: Jun. 26, 2019.
@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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[1] , "CONFIDENCE MEASURES FOR CTC-BASED PHONE SYNCHRONOUS DECODING", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1668. Accessed: Jun. 26, 2019.
@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

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