A Study on Speech Emotion Recognition in the Context of Voice User Experience

被引:0
|
作者
Demaeght, Annebeth [1 ]
Nerb, Josef [2 ]
Mueller, Andrea [1 ]
机构
[1] Hsch Offenburg, Badstr 24, D-77652 Offenburg, Germany
[2] Padagog Hsch Freiburg, Kunzenweg 21, D-79117 Freiburg, Germany
关键词
Voice User Experience; Conversational User Experience; Voice; Assistants; Speech Emotion Recognition; DATABASES; FEATURES;
D O I
10.1007/978-3-031-61318-0_12
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
With the increasing popularity of voice user interfaces (VUIs), there is a growing interest in the evaluation of not only their usability, but also the quality of the user experience (UX). Previous research has shown that UX evaluation in human-machine interaction is significantly influenced by emotions. As a consequence, themeasurement of emotions through the user's speech signalmay enable a better measure of the voice user experience and thus allow for the optimization of human-computer interaction through VUIs. With our study, wewant to contribute to the research on speech emotion recognition in the context of voice user experience. We recorded 45 German participants while they were interacting with a voice assistant in aWizard-of-Oz scenario. The interactions contained some typical user annoyances that might occur in voicebased human-computer interaction. Three analysis modules provided insight into the voice user experience of our participants: (1) a UX-questionnaire; (2) theUEQ+ scales for voice assistants; (3) speech emotion recognition with OpenVokaturi.
引用
收藏
页码:174 / 188
页数:15
相关论文
共 50 条
  • [31] Hybrid Speech Recognition for Voice Search: a Comparative Study
    Gouvea, Evandro
    [J]. 12TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2011 (INTERSPEECH 2011), VOLS 1-5, 2011, : 1120 - 1123
  • [32] A CROSS-CORPUS STUDY ON SPEECH EMOTION RECOGNITION
    Milner, Rosanna
    Jalal, Md Asif
    Ng, Raymond W. M.
    Hain, Thomas
    [J]. 2019 IEEE AUTOMATIC SPEECH RECOGNITION AND UNDERSTANDING WORKSHOP (ASRU 2019), 2019, : 304 - 311
  • [33] A Study of Speech Emotion Recognition Based on Hybrid Algorithm
    Zhu Ju-xia
    Zhang Chao
    Lv Zhao
    Rao Yao-quan
    Wu Xiao-pei
    [J]. INTERNATIONAL CONFERENCE ON GRAPHIC AND IMAGE PROCESSING (ICGIP 2011), 2011, 8285
  • [34] Comparative Study on Normalisation in Emotion Recognition from Speech
    Boeck, Ronald
    Egorow, Olga
    Siegert, Ingo
    Wendemuth, Andreas
    [J]. INTELLIGENT HUMAN COMPUTER INTERACTION, IHCI 2017, 2017, 10688 : 189 - 201
  • [35] STUDY OF DENSE NETWORK APPROACHES FOR SPEECH EMOTION RECOGNITION
    Abdelwahab, Mohammed
    Busso, Carlos
    [J]. 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2018, : 5084 - 5088
  • [36] Emotion recognition in spontaneous emotional speech for anonymity-protected voice chat systems
    Arimoto, Yoshiko
    Kawatsu, Hiromi
    Ohno, Sumio
    Iida, Hitoshi
    [J]. INTERSPEECH 2008: 9TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2008, VOLS 1-5, 2008, : 322 - +
  • [37] Voice Recognition and User Profiling
    Elbaghazaoui, Bahaa Eddine
    Amnai, Mohamed
    Fakhri, Youssef
    [J]. ADVANCES IN CYBERSECURITY, CYBERCRIMES, AND SMART EMERGING TECHNOLOGIES, 2023, 4 : 223 - 233
  • [38] Speech Emotion Recognition using Context-Aware Dilated Convolution Network
    Kakuba, Samuel
    Han, Dong Seog
    [J]. 2022 27TH ASIA PACIFIC CONFERENCE ON COMMUNICATIONS (APCC 2022): CREATING INNOVATIVE COMMUNICATION TECHNOLOGIES FOR POST-PANDEMIC ERA, 2022, : 601 - 604
  • [39] Speech emotion recognition based on emotion perception
    Gang Liu
    Shifang Cai
    Ce Wang
    [J]. EURASIP Journal on Audio, Speech, and Music Processing, 2023
  • [40] Autoencoder With Emotion Embedding for Speech Emotion Recognition
    Zhang, Chenghao
    Xue, Lei
    [J]. IEEE ACCESS, 2021, 9 : 51231 - 51241