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Using affective brain-computer interfaces to characterize human influential factors for speech quality-of-experience perception modelling

机译:使用情感脑机接口来表征人类影响因素,以进行语音体验质量感知建模

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As new speech technologies emerge, telecommunication service providers have to provide superior user experience in order to remain competitive. To this end, quality-of-experience (QoE) perception modelling and measurement has become a key priority. QoE models rely on three influence factors: technological, contextual and human. Existing solutions have typically relied on the former two and human influence factors (HIFs) have been mostly neglected due to difficulty in measuring them. In this paper, we show that measuring human affective states is important for QoE measurement and propose the use of affective brain-computer interfaces (aBCIs) for objective measurement of perceived QoE for two emerging speech technologies, namely far-field hands-free communications and text-to-speech systems. When incorporating subjectively-derived HIFs into the QoE model, gains of up to 26.3?% could be found relative to utilizing only technological factors. When utilizing HIFs derived from an electroencephalography (EEG) based aBCI, in turn, gains of up to 14.5?% were observed. These findings show the importance of using aBCIs in QoE measurement and also highlight that further improvement may be warranted once improved affective state correlates are found from EEGs and/or other neurophysiological modalities.
机译:随着新的语音技术的出现,电信服务提供商必须提供卓越的用户体验,以保持竞争力。为此,体验质量(QoE)感知建模和测量已成为关键优先事项。 QoE模型依赖于三个影响因素:技术,上下文和人为因素。现有的解决方案通常依赖于前两个,而人为影响因素(HIF)由于难以衡量而大多被忽略。在本文中,我们表明测量人的情感状态对于QoE测量很重要,并建议使用情感脑计算机接口(aBCI)客观测量两种新兴语音技术(即远距离免提通信和语音识别)的感知QoE。文字转语音系统。当将主观性的HIF纳入QoE模型时,相对于仅利用技术因素,可以发现高达26.3%的收益。当使用基于脑电图(EEG)的aBCI产生的HIF时,观察到的增益高达14.5%。这些发现表明在QoE测量中使用aBCI的重要性,并且还强调,一旦从EEG和/或其他神经生理学方法中发现了改善的情感状态相关性,则有必要进一步改善。

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