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Computer Sciences, *human – machine relations, Information science (social aspects)
In speech, low frequency regions play a significant role in paralinguistic communication such as the conveyance of emotion or mood. The extent to which lower frequencies signify or contribute to affective speech is still an area for investigation. To investigate paralinguistic cues, and remove interference from linguistic cues, researchers can low-pass filter the speech signal on the assumption that certain acoustic cues characterizing affect are still discernible. Low-pass filtering is a practical technique to investigate paralinguistic phenomena, and is used here to investigate the inference of naturalistic emotional speech. This paper investigates how listeners perceive the level of Activation, and evaluate negative and positive levels, on low-pass filtered naturalistic speech, which has been developed through the use of Mood Inducing Procedures.
Snel, J., Cullen, C. (2013) Judging Emotion from Low-pass Filtered Naturalistic Emotional Speech. Affective Computing and Intelligent Interaction (ACII), Fifth biannual Humaine Association Conference on Affective Computing and Intelligent Interaction, Geneva, Switzerland 2-5, September.