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Measuring Variations of Voice Source and Vocal Tract Characteristics from Korean Emotional Voice

机译:从韩国情感语音中测量语音源和人声道特征的变化

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We explored the voice source and vocal tract characteristics of emotional speech to estimate the voice quality. Emotional speech data used was collected from the actors. Speech materials consist of 10 sentences from 3 male and 3 female speakers in 6 emotional states. 6 emotions are sadness, anger, happiness, fear, boredom and neutral, /a/ sound was segmented from the data used for the analysis. In terms of voice source we measured jitter, shimmer, NHR, pitch and pitch range. To investigate vocal tract changes, normalized vocal tract area ratios were used. Area functions were computed from the linear predictive coefficients. Vocal tract was also divided into three sections to observe the changes according to different emotions. Each computed vocal tract area part was normalized by dividing the same part of corresponding neutral speech. Jitter value was the biggest in the neutral emotion. Shimmer was similar for all the emotions except for the fear. And the fear showed the biggest value in NHR. Pitch value was elevated for all emotions except the boredom. Pitch range was the biggest in the anger. In terms of vocal tract change, there was not a remarkable difference at lip section, but the fear and sadness showed great changes at the vocal fold section
机译:我们探索了情感语音的语音来源和声道特征,以估计语音质量。所使用的情感语音数据是从演员那里收集的。演讲材料包括来自6个情绪状态的3位男性和3位女性演讲者的10句话。 6种情绪是悲伤,愤怒,幸福,恐惧,无聊和中立,/ a /声音是从用于分析的数据中分割出来的。在语音源方面,我们测量了抖动,闪烁,NHR,音调和音调范围。为了研究声道变化,使用归一化声道面积比。从线性预测系数计算面积函数。声道也分为三个部分,根据不同的情绪观察其变化。通过划分相应的中性语音的相同部分来对每个计算出的声道区域部分进行归一化。抖动值是中立情绪中最大的值。除了恐惧之外,所有的情绪都与微光相似。恐惧显示出NHR的最大价值。除了无聊以外,所有情绪的音调值都升高了。音高范围是最大的愤怒。在声道变化方面,唇部没有明显的差异,但恐惧和悲伤在声带中表现出很大的变化

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