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Investigation of glottal features and annotation procedures for speech emotion recognition

机译:语音情感识别的声门特征和标注程序研究

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Speech emotion recognition is a still challenging problem despite having been investigated over the last couple of decades. Conventional speech emotion recognition performance is low, but this may be improved by considering new features and an annotation method. In this paper, firstly we use glottal features for speech emotion recognition to improve its performance because the emotions are related to glottal characteristics. Secondly emotional labels used as “correct” emotions are usually annotated by multiple annotators in the conventional approach, but this may be ambiguous due to the confusion created by using each annotator's criterion. In this paper, a single annotator gives emotional labels in an aim to obtain a unified criterion and we use these labels for speech emotion recognition to improve its performance. Finally, context information which is included in a speech segment before the utterance being annotated, will be considered.
机译:尽管在过去的几十年中进行了研究,但语音情感识别仍是一个具有挑战性的问题。常规的语音情感识别性能较低,但是可以通过考虑新功能和注释方法来改进。在本文中,由于情感与声门特征有关,因此我们首先使用声门特征进行语音情感识别,以提高其性能。其次,在常规方法中,通常使用多个注释者来注释用作“正确”情绪的情绪标签,但是由于使用每个注释者的标准所造成的混淆,这可能是模棱两可的。在本文中,单个注释器给出了情感标签,旨在获得统一的标准,并且我们将这些标签用于语音情感识别以提高其性能。最后,将考虑在注释话语之前包括在语音段中的上下文信息。

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