The production and recognition of emotions in speech: features and algorithms

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Primitives-based evaluation and estimation of emotions in speech (2007, unknown): “Other examples of relevant work include (Dellaert et al., 1996; Batliner et al., 2000; Oudeyer, 2003; Nwe et al., 2003; Ververidis et al., 2004).”
Human-Computer Interaction: Overview on State of the Art (2008, unknown): “interaction initiated the efforts in analysis of emotions in audio signals [ 48 ] [49].”
Multimodal Human Computer Interaction: A Survey (2005, background): “Traditional as well as most recent studies on emotional contents in speech (see [ 46 ], [95], and [68]) use “prosodic” information which includes the pitch, duration, and intensity of the utterance.”
Speech Emotion Recognition from Spectrograms with Deep Convolutional Neural Network (2017, background): “It is believed that, SER can be used to extract useful semantics from speech, as well as improve the performance of speech recognition system [3].”
Modeling naturalistic affective states via facial and vocal expressions recognition (2006, background): “All information related to emotion that one can extract from pitch is probably not only in these features, but the motivation of this approach is in the desire to develop and use a high level of speech prosody analysis, calculate as many features as possible and then reduce them to those uncorrelate”