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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/16077

Title: Speech Emotion Recognition Based on Speech Segment Using LSTM with Attention Model
Authors: Atmaja, Bagus Tris
Akagi, Masato
Keywords: voice segments
silence removal
speech emotion recognition
attention model
Issue Date: 2019-07-16
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Magazine name: 2019 IEEE International Conference on Signals and Systems (ICSigSys)
DOI: 10.1109/ICSIGSYS.2019.8811080
Abstract: Automatic speech emotion recognition has become popular as it enables natural interaction between human-machine interaction. One modality of recognizing emotion is speech. However, the speech also contains silence that may not relevant to emotion. Two ways to improve performance is by removing silence and/or paying more attention to speech segment while ignoring the silence. In this paper, we propose both, a combination of silence removal and attention model to improve speech emotion recognition performance. The results show that utilizing combination silence removal and attention model outperforms the use of either noise removal only or attention model only.
Rights: This is the author's version of the work. Copyright (C) 2019 IEEE. 2019 IEEE International Conference on Signals and Systems (ICSigSys), 2019, DOI:10.1109/ICSIGSYS.2019.8811080. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
URI: http://hdl.handle.net/10119/16077
Material Type: author
Appears in Collections:b11-1. 会議発表論文・発表資料 (Conference Papers)

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