Abstract
Paralinguistic cues are the non-phonemic aspects of human speech that convey information about the affective state of the speaker. In children's speech, these events are also important markers for the detection of early developmental disorders. Detecting these events in hours of audio data would be beneficial for clinicians to analyze the social behaviors of children. The chapter focuses on the use of spectral and prosodic baseline acoustic features to classify instances of children's laughter and fussing/crying while interacting with their caregivers in naturalistic settings. In conjunction with baseline features, long-term intensity-based features, that capture the periodic structure of laughter, enable in detecting instances of laughter to a reasonably high degree of accuracy in a variety of classification tasks.
| Original language | English (US) |
|---|---|
| Title of host publication | Mobile Health |
| Subtitle of host publication | Sensors, Analytic Methods, and Applications |
| Publisher | Springer International Publishing |
| Pages | 219-238 |
| Number of pages | 20 |
| ISBN (Electronic) | 9783319513942 |
| ISBN (Print) | 9783319513935 |
| DOIs | |
| State | Published - Jul 12 2017 |
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ASJC Scopus subject areas
- Medicine(all)
- Computer Science(all)
Cite this
Paralinguistic analysis of children's speech in natural environments. / Rao, Hrishikesh; Clements, Mark A.; Li, Yin; Swanson, Meghan R.; Piven, Joseph; Messinger, Daniel S.
Mobile Health: Sensors, Analytic Methods, and Applications. Springer International Publishing, 2017. p. 219-238.Research output: Chapter in Book/Report/Conference proceeding › Chapter
}
TY - CHAP
T1 - Paralinguistic analysis of children's speech in natural environments
AU - Rao, Hrishikesh
AU - Clements, Mark A.
AU - Li, Yin
AU - Swanson, Meghan R.
AU - Piven, Joseph
AU - Messinger, Daniel S
PY - 2017/7/12
Y1 - 2017/7/12
N2 - Paralinguistic cues are the non-phonemic aspects of human speech that convey information about the affective state of the speaker. In children's speech, these events are also important markers for the detection of early developmental disorders. Detecting these events in hours of audio data would be beneficial for clinicians to analyze the social behaviors of children. The chapter focuses on the use of spectral and prosodic baseline acoustic features to classify instances of children's laughter and fussing/crying while interacting with their caregivers in naturalistic settings. In conjunction with baseline features, long-term intensity-based features, that capture the periodic structure of laughter, enable in detecting instances of laughter to a reasonably high degree of accuracy in a variety of classification tasks.
AB - Paralinguistic cues are the non-phonemic aspects of human speech that convey information about the affective state of the speaker. In children's speech, these events are also important markers for the detection of early developmental disorders. Detecting these events in hours of audio data would be beneficial for clinicians to analyze the social behaviors of children. The chapter focuses on the use of spectral and prosodic baseline acoustic features to classify instances of children's laughter and fussing/crying while interacting with their caregivers in naturalistic settings. In conjunction with baseline features, long-term intensity-based features, that capture the periodic structure of laughter, enable in detecting instances of laughter to a reasonably high degree of accuracy in a variety of classification tasks.
UR - http://www.scopus.com/inward/record.url?scp=85055379839&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85055379839&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-51394-2_12
DO - 10.1007/978-3-319-51394-2_12
M3 - Chapter
AN - SCOPUS:85055379839
SN - 9783319513935
SP - 219
EP - 238
BT - Mobile Health
PB - Springer International Publishing
ER -