Title :
Emotion recognition from the human voice
Author :
Parlak, C. ; Diri, B.
Author_Institution :
Bilgisayar Muhendisligi Bolumu, Yildiz Teknik Univ., Istanbul, Turkey
Abstract :
Speech is the most important communication tool between humans and is thousands of years old. As known human voice is a biometric feature like fingerprint and carries the emotional state of the speaker. Therefore, speech data acquired from live talks may have more realistic emotional features than textual data. In this work, we will try to determine whether a speaker independent speech is angry, neutral, happy or sad.
Keywords :
feature extraction; speaker recognition; biometric feature; communication tool; emotion recognition; human voice; realistic emotional features; speaker independent speech; speech data; textual data; Emotion recognition; Fingerprint recognition; Human voice; Mel frequency cepstral coefficient; Speech; Speech recognition; Emotion Analysis; Emotion Mining; Pitch; Prosody;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2013 21st
Conference_Location :
Haspolat
Print_ISBN :
978-1-4673-5562-9
Electronic_ISBN :
978-1-4673-5561-2
DOI :
10.1109/SIU.2013.6531196
