Abstract
This study was designed to introduce a kind of novel speech emotional features extracted from Electroglot-tography (EGG). These features were obtained from the power-law distribution coefficient (PLDC) of fundamental frequency (F 0) and duration parameters. First, the segments of silence, voiced and unvoiced (SUV) were distinguished by combining the EGG and speech information. Second, the F 0 of voiced segment and the first-order differential of F 0 was obtained by a cepstrum method. Third, PLDC of voiced segment as well as the pitch rise and pitch down duration were calculated. Simulation results show that the proposed features are closely connected with emotions. Experiments based on Support Vector Machine (SV M) are carried out. The results show that proposed features are better than those commonly used in the case of speaker independent emotion recognition.
| Original language | English |
|---|---|
| Title of host publication | BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing |
| Pages | 131-136 |
| Number of pages | 6 |
| Publication status | Published - 2012 |
| Externally published | Yes |
| Event | International Conference on Bio-inspired Systems and Signal Processing, BIOSIGNALS 2012 - Vilamoura, Algarve Duration: 2012 Feb 1 → 2012 Feb 4 |
Other
| Other | International Conference on Bio-inspired Systems and Signal Processing, BIOSIGNALS 2012 |
|---|---|
| City | Vilamoura, Algarve |
| Period | 12/2/1 → 12/2/4 |
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Keywords
- Electroglottography
- Power-law distribution
- Speech emotional features
ASJC Scopus subject areas
- Signal Processing
Cite this
Speech emotional features measured by power-law distribution based on electroglottography. / Chen, Lijiang; Mao, Xia; Xue, Yuli; Ishizuka, Mitsuru.
BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing. 2012. p. 131-136.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Speech emotional features measured by power-law distribution based on electroglottography
AU - Chen, Lijiang
AU - Mao, Xia
AU - Xue, Yuli
AU - Ishizuka, Mitsuru
PY - 2012
Y1 - 2012
N2 - This study was designed to introduce a kind of novel speech emotional features extracted from Electroglot-tography (EGG). These features were obtained from the power-law distribution coefficient (PLDC) of fundamental frequency (F 0) and duration parameters. First, the segments of silence, voiced and unvoiced (SUV) were distinguished by combining the EGG and speech information. Second, the F 0 of voiced segment and the first-order differential of F 0 was obtained by a cepstrum method. Third, PLDC of voiced segment as well as the pitch rise and pitch down duration were calculated. Simulation results show that the proposed features are closely connected with emotions. Experiments based on Support Vector Machine (SV M) are carried out. The results show that proposed features are better than those commonly used in the case of speaker independent emotion recognition.
AB - This study was designed to introduce a kind of novel speech emotional features extracted from Electroglot-tography (EGG). These features were obtained from the power-law distribution coefficient (PLDC) of fundamental frequency (F 0) and duration parameters. First, the segments of silence, voiced and unvoiced (SUV) were distinguished by combining the EGG and speech information. Second, the F 0 of voiced segment and the first-order differential of F 0 was obtained by a cepstrum method. Third, PLDC of voiced segment as well as the pitch rise and pitch down duration were calculated. Simulation results show that the proposed features are closely connected with emotions. Experiments based on Support Vector Machine (SV M) are carried out. The results show that proposed features are better than those commonly used in the case of speaker independent emotion recognition.
KW - Electroglottography
KW - Power-law distribution
KW - Speech emotional features
UR - http://www.scopus.com/inward/record.url?scp=84861966782&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84861966782&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84861966782
SN - 9789898425898
SP - 131
EP - 136
BT - BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing
ER -