Emotional recognition from the speech signal for a virtual education agent

Andrew Jason Tickle, S Raghu, Mark Elshaw

Research output: Contribution to journalConference articlepeer-review

14 Citations (Scopus)
4 Downloads (Pure)


This paper explores the extraction of features from the speech wave to perform intelligent emotion recognition. A feature extract tool (openSmile) was used to obtain a baseline set of 998 acoustic features from a set of emotional speech recordings from amicrophone. The initial features were reduced to the most important ones so recognition ofemotions using a supervised neural network could be performed. Given that the future use of virtual education agents lies with making the agents more interactive, developing agents with the capability to recognise and adapt to the emotional state of humans is an important step.
Original languageEnglish
Article number012053
Number of pages7
JournalJournal of Physics: Conference Series
Publication statusPublished - 2013
EventSensors & Their Applications XVII 2013 - Dubrovnik, Croatia
Duration: 16 Sep 201318 Sep 2013
Conference number: 17

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