Effect of Reverberation in Speech-based Emotion Recognition

Shujie Zhao; Yan Yang; Jingdong Chen

doi:10.1109/ICSEE.2018.8645989

Effect of Reverberation in Speech-based Emotion Recognition

Shujie Zhao, Yan Yang, Jingdong Chen

School of Marine Science and Technology

Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

In room environment, echo, reverberation, interference and additive noise cast the major challenges for emotional speech recognition due to degradation in quality and reliability of recorded speech signals. In this paper, we investigate effects of reverberation and noise on speech-based emotion recognition by comparing clean speech signal, adding simulated reverberant data, de-reverberant data and signal with added noise. First, we develop an emotional speech corpus of these four kinds of emotional speech data sources. Then we apply GMM-UBM framework to evaluate the performance of emotion recognition based on them. Results show that reverberation reduces emotion recognition accuracy by 5.87%, and a process of de-reverberation can largely cover this reduction.

Original language	English
Title of host publication	2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538663783
DOIs	https://doi.org/10.1109/ICSEE.2018.8645989
State	Published - 2 Jul 2018
Event	2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018 - Eilat, Israel Duration: 12 Dec 2018 → 14 Dec 2018

Publication series

Name	2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018

Conference

Conference	2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
Country/Territory	Israel
City	Eilat
Period	12/12/18 → 14/12/18

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10.1109/ICSEE.2018.8645989

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Zhao, S., Yang, Y., & Chen, J. (2018). Effect of Reverberation in Speech-based Emotion Recognition. In 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018 Article 8645989 (2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSEE.2018.8645989

@inproceedings{7fe3bc6656d74c95b707c3edb577a082,

title = "Effect of Reverberation in Speech-based Emotion Recognition",

abstract = "In room environment, echo, reverberation, interference and additive noise cast the major challenges for emotional speech recognition due to degradation in quality and reliability of recorded speech signals. In this paper, we investigate effects of reverberation and noise on speech-based emotion recognition by comparing clean speech signal, adding simulated reverberant data, de-reverberant data and signal with added noise. First, we develop an emotional speech corpus of these four kinds of emotional speech data sources. Then we apply GMM-UBM framework to evaluate the performance of emotion recognition based on them. Results show that reverberation reduces emotion recognition accuracy by 5.87%, and a process of de-reverberation can largely cover this reduction.",

author = "Shujie Zhao and Yan Yang and Jingdong Chen",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018 ; Conference date: 12-12-2018 Through 14-12-2018",

year = "2018",

month = jul,

day = "2",

doi = "10.1109/ICSEE.2018.8645989",

language = "英语",

series = "2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018",

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booktitle = "2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018",

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Zhao, S, Yang, Y & Chen, J 2018, Effect of Reverberation in Speech-based Emotion Recognition. in 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018., 8645989, 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018, Institute of Electrical and Electronics Engineers Inc., 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018, Eilat, Israel, 12/12/18. https://doi.org/10.1109/ICSEE.2018.8645989

Effect of Reverberation in Speech-based Emotion Recognition. / Zhao, Shujie; Yang, Yan; Chen, Jingdong.
2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8645989 (2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2018/7/2

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N2 - In room environment, echo, reverberation, interference and additive noise cast the major challenges for emotional speech recognition due to degradation in quality and reliability of recorded speech signals. In this paper, we investigate effects of reverberation and noise on speech-based emotion recognition by comparing clean speech signal, adding simulated reverberant data, de-reverberant data and signal with added noise. First, we develop an emotional speech corpus of these four kinds of emotional speech data sources. Then we apply GMM-UBM framework to evaluate the performance of emotion recognition based on them. Results show that reverberation reduces emotion recognition accuracy by 5.87%, and a process of de-reverberation can largely cover this reduction.

AB - In room environment, echo, reverberation, interference and additive noise cast the major challenges for emotional speech recognition due to degradation in quality and reliability of recorded speech signals. In this paper, we investigate effects of reverberation and noise on speech-based emotion recognition by comparing clean speech signal, adding simulated reverberant data, de-reverberant data and signal with added noise. First, we develop an emotional speech corpus of these four kinds of emotional speech data sources. Then we apply GMM-UBM framework to evaluate the performance of emotion recognition based on them. Results show that reverberation reduces emotion recognition accuracy by 5.87%, and a process of de-reverberation can largely cover this reduction.

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M3 - 会议稿件

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BT - 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018

PB - Institute of Electrical and Electronics Engineers Inc.

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Zhao S, Yang Y, Chen J. Effect of Reverberation in Speech-based Emotion Recognition. In 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8645989. (2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018). doi: 10.1109/ICSEE.2018.8645989

Effect of Reverberation in Speech-based Emotion Recognition

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