DocumentCode :
3530022
Title :
Investigating glottal parameters for differentiating emotional categories with similar prosodics
Author :
Sun, Rui ; Moore, Elliot, II ; Torres, Juan F.
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Savannah, GA
fYear :
2009
fDate :
19-24 April 2009
Firstpage :
4509
Lastpage :
4512
Abstract :
Speech prosodics (i.e., pitch, energy, etc.) play an important role in the interpretation of emotional expression. However, certain pairs of emotions can be difficult to discriminate due to similar displayed tendencies in prosodic statistics. The purpose of this paper is to target speaker dependent expressions of emotional pairs that share statistically similar prosodic information and investigate a set of glottal features for their ability to find measurable differences in these expressions. Evaluation is based on acted emotional utterances from the emotional prosody and speech transcript (EPST) database. While it is in no way assumed that acted speech provides a complete picture of authentic emotion, the value of this information is that the actors adjusted their voice quality to fit their perception of different emotions. Results show statistically significant differences (p < 0.05) in at least one glottal feature for all 30 emotion pairs where prosodic features did not show a significant difference. In addition, the use of single glottal features reduced classification error for 24 emotion pairs in comparison to pitch or energy.
Keywords :
emotion recognition; speaker recognition; speech processing; statistics; emotional categories; emotional expression; emotional prosody; glottal parameters; prosodic statistics; speaker dependent expressions; speech prosodics; speech transcript; Algorithm design and analysis; Computer errors; Feature extraction; Higher order statistics; Human computer interaction; Power engineering and energy; Sampling methods; Spatial databases; Speech analysis; Sun; Affect; Emotion; Glottal; Pitch; Prosodics; Speech;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location :
Taipei
ISSN :
1520-6149
Print_ISBN :
978-1-4244-2353-8
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2009.4960632
Filename :
4960632
Link To Document :
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