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WASPAA 2019

IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA). The WASPAA meeting is a traditional event supported by the Audio and Acoustic Signal Processing Committee of the IEEE Signal Processing Society. The first WASPAA meeting was convened in 1986 and since 1989 it has been held every other year.

Regression versus classification for neural network based audio source localization

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Authors:
Lauréline Perotin, Alexandre Défossez, Emmanuel Vincent, Romain Serizel, Alexandre Guérin
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24 October 2019 - 11:45am
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poster_v2.pdf

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[1] Lauréline Perotin, Alexandre Défossez, Emmanuel Vincent, Romain Serizel, Alexandre Guérin, "Regression versus classification for neural network based audio source localization", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4888. Accessed: Nov. 15, 2019.
@article{4888-19,
url = {http://sigport.org/4888},
author = {Lauréline Perotin; Alexandre Défossez; Emmanuel Vincent; Romain Serizel; Alexandre Guérin },
publisher = {IEEE SigPort},
title = {Regression versus classification for neural network based audio source localization},
year = {2019} }
TY - EJOUR
T1 - Regression versus classification for neural network based audio source localization
AU - Lauréline Perotin; Alexandre Défossez; Emmanuel Vincent; Romain Serizel; Alexandre Guérin
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4888
ER -
Lauréline Perotin, Alexandre Défossez, Emmanuel Vincent, Romain Serizel, Alexandre Guérin. (2019). Regression versus classification for neural network based audio source localization. IEEE SigPort. http://sigport.org/4888
Lauréline Perotin, Alexandre Défossez, Emmanuel Vincent, Romain Serizel, Alexandre Guérin, 2019. Regression versus classification for neural network based audio source localization. Available at: http://sigport.org/4888.
Lauréline Perotin, Alexandre Défossez, Emmanuel Vincent, Romain Serizel, Alexandre Guérin. (2019). "Regression versus classification for neural network based audio source localization." Web.
1. Lauréline Perotin, Alexandre Défossez, Emmanuel Vincent, Romain Serizel, Alexandre Guérin. Regression versus classification for neural network based audio source localization [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4888

A CLASSIFICATION-AIDED FRAMEWORK FOR NON-INTRUSIVE SPEECH QUALITY ASSESSMENT


Objective metrics, such as the perceptual evaluation of speech quality (PESQ) have become standard measures for evaluating speech. These metrics enable efficient and costless evaluations, where ratings are often computed by comparing a degraded speech signal to its underlying clean reference signal. Reference-based metrics, however, cannot be used to evaluate real-world signals that have inaccessible references. This project develops a nonintrusive framework for evaluating the perceptual quality of noisy and enhanced speech.

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Authors:
Xuan Dong, Donald Williamson
Submitted On:
21 October 2019 - 2:28pm
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[1] Xuan Dong, Donald Williamson, "A CLASSIFICATION-AIDED FRAMEWORK FOR NON-INTRUSIVE SPEECH QUALITY ASSESSMENT", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4883. Accessed: Nov. 15, 2019.
@article{4883-19,
url = {http://sigport.org/4883},
author = {Xuan Dong; Donald Williamson },
publisher = {IEEE SigPort},
title = {A CLASSIFICATION-AIDED FRAMEWORK FOR NON-INTRUSIVE SPEECH QUALITY ASSESSMENT},
year = {2019} }
TY - EJOUR
T1 - A CLASSIFICATION-AIDED FRAMEWORK FOR NON-INTRUSIVE SPEECH QUALITY ASSESSMENT
AU - Xuan Dong; Donald Williamson
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4883
ER -
Xuan Dong, Donald Williamson. (2019). A CLASSIFICATION-AIDED FRAMEWORK FOR NON-INTRUSIVE SPEECH QUALITY ASSESSMENT. IEEE SigPort. http://sigport.org/4883
Xuan Dong, Donald Williamson, 2019. A CLASSIFICATION-AIDED FRAMEWORK FOR NON-INTRUSIVE SPEECH QUALITY ASSESSMENT. Available at: http://sigport.org/4883.
Xuan Dong, Donald Williamson. (2019). "A CLASSIFICATION-AIDED FRAMEWORK FOR NON-INTRUSIVE SPEECH QUALITY ASSESSMENT." Web.
1. Xuan Dong, Donald Williamson. A CLASSIFICATION-AIDED FRAMEWORK FOR NON-INTRUSIVE SPEECH QUALITY ASSESSMENT [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4883

Speech enhancement Using Polynomial Eigenvalue Decomposition


Speech enhancement is important for applications such as telecommunications, hearing aids, automatic speech recognition and voice-controlled system. The enhancement algorithms aim to reduce interfering noise while minimizing any speech distortion. In this work for speech enhancement, we propose to use polynomial matrices in order to exploit the spatial, spectral as well as temporal correlations between the speech signals received by the microphone array.

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Authors:
Christine Evers, Patrick A. Naylor
Submitted On:
5 November 2019 - 6:16am
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[1] Christine Evers, Patrick A. Naylor, "Speech enhancement Using Polynomial Eigenvalue Decomposition", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4882. Accessed: Nov. 15, 2019.
@article{4882-19,
url = {http://sigport.org/4882},
author = {Christine Evers; Patrick A. Naylor },
publisher = {IEEE SigPort},
title = {Speech enhancement Using Polynomial Eigenvalue Decomposition},
year = {2019} }
TY - EJOUR
T1 - Speech enhancement Using Polynomial Eigenvalue Decomposition
AU - Christine Evers; Patrick A. Naylor
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4882
ER -
Christine Evers, Patrick A. Naylor. (2019). Speech enhancement Using Polynomial Eigenvalue Decomposition. IEEE SigPort. http://sigport.org/4882
Christine Evers, Patrick A. Naylor, 2019. Speech enhancement Using Polynomial Eigenvalue Decomposition. Available at: http://sigport.org/4882.
Christine Evers, Patrick A. Naylor. (2019). "Speech enhancement Using Polynomial Eigenvalue Decomposition." Web.
1. Christine Evers, Patrick A. Naylor. Speech enhancement Using Polynomial Eigenvalue Decomposition [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4882

Analytical Method of 2.5D Exterior Sound Field Synthesis by Using Multipole Loudspeaker Array


We propose an analytical method of 2.5-dimensional exterior sound field reproduction by using a multipole loudspeaker array. The method reproduces the sound field modeled by expansion coefficients of spherical harmonics based on multipole superposition. We also present an analytical method for converting the expansion coefficients of spherical harmonics to weighting coefficients for multipole superposition.

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Authors:
Kenta Imaizumi, Kimitaka Tsuitsuimi, Atsushi Nakadaira, Yoichi Haneda
Submitted On:
18 October 2019 - 1:47am
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WASPAA2019_Poster_Imaizumi.pdf

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[1] Kenta Imaizumi, Kimitaka Tsuitsuimi, Atsushi Nakadaira, Yoichi Haneda, "Analytical Method of 2.5D Exterior Sound Field Synthesis by Using Multipole Loudspeaker Array", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4880. Accessed: Nov. 15, 2019.
@article{4880-19,
url = {http://sigport.org/4880},
author = {Kenta Imaizumi; Kimitaka Tsuitsuimi; Atsushi Nakadaira; Yoichi Haneda },
publisher = {IEEE SigPort},
title = {Analytical Method of 2.5D Exterior Sound Field Synthesis by Using Multipole Loudspeaker Array},
year = {2019} }
TY - EJOUR
T1 - Analytical Method of 2.5D Exterior Sound Field Synthesis by Using Multipole Loudspeaker Array
AU - Kenta Imaizumi; Kimitaka Tsuitsuimi; Atsushi Nakadaira; Yoichi Haneda
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4880
ER -
Kenta Imaizumi, Kimitaka Tsuitsuimi, Atsushi Nakadaira, Yoichi Haneda. (2019). Analytical Method of 2.5D Exterior Sound Field Synthesis by Using Multipole Loudspeaker Array. IEEE SigPort. http://sigport.org/4880
Kenta Imaizumi, Kimitaka Tsuitsuimi, Atsushi Nakadaira, Yoichi Haneda, 2019. Analytical Method of 2.5D Exterior Sound Field Synthesis by Using Multipole Loudspeaker Array. Available at: http://sigport.org/4880.
Kenta Imaizumi, Kimitaka Tsuitsuimi, Atsushi Nakadaira, Yoichi Haneda. (2019). "Analytical Method of 2.5D Exterior Sound Field Synthesis by Using Multipole Loudspeaker Array." Web.
1. Kenta Imaizumi, Kimitaka Tsuitsuimi, Atsushi Nakadaira, Yoichi Haneda. Analytical Method of 2.5D Exterior Sound Field Synthesis by Using Multipole Loudspeaker Array [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4880

3D localized sound zone generation with a planar omni-directional loudspeaker array


This paper provides a 3D localized sound zone generation method using a planar omni-directional loudspeaker array. In the proposed method, multiple co-centered circular arrays are arranged on the horizontal plane and an additional loudspeaker is located at the array’s center. The sound field produced by this center loudspeaker is then cancelled using the multiple circular arrays. A localized 3D sound zone can thus be generated inside a sphere with a maximum radius of that of the circular arrays because the residual sound field is contained within the sphere.

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Submitted On:
17 October 2019 - 1:25am
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WASPAA_2019_okamoto.pdf

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[1] , "3D localized sound zone generation with a planar omni-directional loudspeaker array", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4877. Accessed: Nov. 15, 2019.
@article{4877-19,
url = {http://sigport.org/4877},
author = { },
publisher = {IEEE SigPort},
title = {3D localized sound zone generation with a planar omni-directional loudspeaker array},
year = {2019} }
TY - EJOUR
T1 - 3D localized sound zone generation with a planar omni-directional loudspeaker array
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4877
ER -
. (2019). 3D localized sound zone generation with a planar omni-directional loudspeaker array. IEEE SigPort. http://sigport.org/4877
, 2019. 3D localized sound zone generation with a planar omni-directional loudspeaker array. Available at: http://sigport.org/4877.
. (2019). "3D localized sound zone generation with a planar omni-directional loudspeaker array." Web.
1. . 3D localized sound zone generation with a planar omni-directional loudspeaker array [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4877

WASPAA 2019 POSTER: MULTIPLE HYPOTHESIS TRACKING FOR OVERLAPPING SPEAKER SEGMENTATION


Speaker segmentation is an essential part of any diarization system.Applications of diarization include tasks such as speaker indexing, improving automatic speech recognition (ASR) performance and making single speaker-based algorithms available for use in multi-speaker environments.This paper proposes a multiple hypothesis tracking (MHT) method that exploits the harmonic structure associated with the pitch in voiced speech in order to segment the onsets and end-points of speech from multiple, overlapping speakers.

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Authors:
Aidan O. T. Hogg, Christine Evers, Patrick A. Naylor
Submitted On:
16 October 2019 - 7:03am
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[1] Aidan O. T. Hogg, Christine Evers, Patrick A. Naylor, "WASPAA 2019 POSTER: MULTIPLE HYPOTHESIS TRACKING FOR OVERLAPPING SPEAKER SEGMENTATION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4874. Accessed: Nov. 15, 2019.
@article{4874-19,
url = {http://sigport.org/4874},
author = {Aidan O. T. Hogg; Christine Evers; Patrick A. Naylor },
publisher = {IEEE SigPort},
title = {WASPAA 2019 POSTER: MULTIPLE HYPOTHESIS TRACKING FOR OVERLAPPING SPEAKER SEGMENTATION},
year = {2019} }
TY - EJOUR
T1 - WASPAA 2019 POSTER: MULTIPLE HYPOTHESIS TRACKING FOR OVERLAPPING SPEAKER SEGMENTATION
AU - Aidan O. T. Hogg; Christine Evers; Patrick A. Naylor
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4874
ER -
Aidan O. T. Hogg, Christine Evers, Patrick A. Naylor. (2019). WASPAA 2019 POSTER: MULTIPLE HYPOTHESIS TRACKING FOR OVERLAPPING SPEAKER SEGMENTATION. IEEE SigPort. http://sigport.org/4874
Aidan O. T. Hogg, Christine Evers, Patrick A. Naylor, 2019. WASPAA 2019 POSTER: MULTIPLE HYPOTHESIS TRACKING FOR OVERLAPPING SPEAKER SEGMENTATION. Available at: http://sigport.org/4874.
Aidan O. T. Hogg, Christine Evers, Patrick A. Naylor. (2019). "WASPAA 2019 POSTER: MULTIPLE HYPOTHESIS TRACKING FOR OVERLAPPING SPEAKER SEGMENTATION." Web.
1. Aidan O. T. Hogg, Christine Evers, Patrick A. Naylor. WASPAA 2019 POSTER: MULTIPLE HYPOTHESIS TRACKING FOR OVERLAPPING SPEAKER SEGMENTATION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4874

An Improved Measure of Musical Noise Based on Spectral Kurtosis


Audio processing methods operating on a time-frequency representation of the signal can introduce unpleasant sounding artifacts known as musical noise. These artifacts are observed in the context of audio coding, speech enhancement, and source separation. The change in kurtosis of the power spectrum introduced during the processing was shown to correlate with the human perception of musical noise in the context of speech enhancement, leading to the proposal of measures based on it. These baseline measures are here shown to correlate with human perception only in a limited manner.

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Authors:
Matteo Torcoli
Submitted On:
14 October 2019 - 3:13am
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[1] Matteo Torcoli, "An Improved Measure of Musical Noise Based on Spectral Kurtosis", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4868. Accessed: Nov. 15, 2019.
@article{4868-19,
url = {http://sigport.org/4868},
author = {Matteo Torcoli },
publisher = {IEEE SigPort},
title = {An Improved Measure of Musical Noise Based on Spectral Kurtosis},
year = {2019} }
TY - EJOUR
T1 - An Improved Measure of Musical Noise Based on Spectral Kurtosis
AU - Matteo Torcoli
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4868
ER -
Matteo Torcoli. (2019). An Improved Measure of Musical Noise Based on Spectral Kurtosis. IEEE SigPort. http://sigport.org/4868
Matteo Torcoli, 2019. An Improved Measure of Musical Noise Based on Spectral Kurtosis. Available at: http://sigport.org/4868.
Matteo Torcoli. (2019). "An Improved Measure of Musical Noise Based on Spectral Kurtosis." Web.
1. Matteo Torcoli. An Improved Measure of Musical Noise Based on Spectral Kurtosis [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4868