scholarly journals Cryprint Categories in Newborn‐Infant Cry‐Sound Analysis

1967 ◽  
Vol 42 (5) ◽  
pp. 1164-1164
Author(s):  
H. M. Truby
Keyword(s):  
Newborn Infant ◽  
Sound Analysis ◽  
Infant Cry

The Newborn Infant Cry

Infant Crying ◽  
1985 ◽  
pp. 119-137 ◽  
Author(s):  
Raymond H. Colton ◽  
Alfred Steinschneider ◽  
Lois Black ◽  
John Gleason
Keyword(s):  
Newborn Infant ◽  
Infant Cry

Acoustic analysis of newborn infant cry signals

1998 ◽  
Vol 20 (6) ◽  
pp. 432-442 ◽  
Author(s):  
Ada Fort ◽  
Claudia Manfredi
Keyword(s):  
Newborn Infant ◽  
Acoustic Analysis ◽  
Infant Cry

Phonation in the newborn, infant cry

1999 ◽  
Vol 49 ◽  
pp. S297-S301 ◽  
Author(s):  
Katarina Michelsson ◽  
Oliver Michelsson
Keyword(s):  
Newborn Infant ◽  
Infant Cry

NEWBORN INFANT CRY AND NONHUMAN-PRIMATE VOCALIZATIONS

1972 ◽  
pp. 41-53
Author(s):  
Philip Lieberman ◽  
Katherine S. Harris ◽  
Peter Wolff ◽  
Lorraine H. Russell
Keyword(s):  
Newborn Infant ◽  
Nonhuman Primate ◽  
Infant Cry ◽  
Primate Vocalizations

Enhanced Estimation of Speech Formants in Newborn Infant Cry

1997 ◽  
Vol 30 (2) ◽  
pp. 309-314
Author(s):  
A. Fort ◽  
C. Manfredi
Keyword(s):  
Newborn Infant ◽  
Infant Cry

scholarly journals An Efficient Classification of Neonates Cry Using Extreme Gradient Boosting-Assisted Grouped-Support-Vector Network

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Chuan-Yu Chang ◽  
Sweta Bhattacharya ◽  
P. M. Durai Raj Vincent ◽  
Kuruva Lakshmanna ◽  
Kathiravan Srinivasan
Keyword(s):  
Newborn Infant ◽  
Recognition Rate ◽  
Gradient Boosting ◽  
Support Vector ◽  
Acoustic Feature ◽  
Infant Cry ◽  
Fast Recognition ◽  
Extreme Gradient Boosting ◽  
Infant Cries

The cry is a loud, high pitched verbal communication of infants. The very high fundamental frequency and resonance frequency characterize a neonatal infant cry having certain sudden variations. Furthermore, in a tiny duration solitary utterance, the cry signal also possesses both voiced and unvoiced features. Mostly, infants communicate with their caretakers through cries, and sometimes, it becomes difficult for the caretakers to comprehend the reason behind the newborn infant cry. As a result, this research proposes a novel work for classifying the newborn infant cries under three groups such as hunger, sleep, and discomfort. For each crying frame, twelve features get extracted through acoustic feature engineering, and the variable selection using random forests was used for selecting the highly discriminative features among the twelve time and frequency domain features. Subsequently, the extreme gradient boosting-powered grouped-support-vector network is deployed for neonate cry classification. The empirical results show that the proposed method could effectively classify the neonate cries under three different groups. The finest experimental results showed a mean accuracy of around 91% for most scenarios, and this exhibits the potential of the proposed extreme gradient boosting-powered grouped-support-vector network in neonate cry classification. Also, the proposed method has a fast recognition rate of 27 seconds in the identification of these emotional cries.

Newborn Infant Cry (Supplement 163).

1966 ◽  
Vol 15 (4) ◽  
pp. 446
Author(s):  
Peter F. Ostwald
Keyword(s):  
Newborn Infant ◽  
Infant Cry

scholarly journals Newborn Infant Cry in Relation to Nonhuman Primate Vocalizations

1968 ◽  
Vol 44 (1) ◽  
pp. 365-365 ◽  
Author(s):  
Philip Lieberman ◽  
Katherine S. Harris ◽  
Peter Wolff
Keyword(s):  
Newborn Infant ◽  
Nonhuman Primate ◽  
Infant Cry ◽  
Primate Vocalizations
Sign in / Sign up

Export Citation Format

Share Document