Acoustic measures of the cry characteristics of healthy newborns and newborns with pathologies
Affiliation(s)
Department of Electrical Engineering, école de Technologie Supérieure, Montreal, Canada.
Department of Electrical Engineering, école de Technologie Supérieure, Montreal, Canada.
ABSTRACT
Several hypotheses have been formulated as a result of observing spectrograms of the audio signals of the newborn infant cry in numerous studies. Our study is based on a few of these hypotheses. The purpose of this article is to differentiate pathological crying from healthy crying through acoustic cry analysis based on neurophysiological parameters of newborns. The automatic estimation of the characteristics of relevant cry signals, such as phonation, hyperphonation, and dysphonation, expressed as percentages, as well as unvoiced sound and mode change percentages, have enabled us to distinguish among the pathologies selected for this study. The results obtained have helped us to make quantitative associations between cry characteristics and pathological conditions affecting newborns.
Several hypotheses have been formulated as a result of observing spectrograms of the audio signals of the newborn infant cry in numerous studies. Our study is based on a few of these hypotheses. The purpose of this article is to differentiate pathological crying from healthy crying through acoustic cry analysis based on neurophysiological parameters of newborns. The automatic estimation of the characteristics of relevant cry signals, such as phonation, hyperphonation, and dysphonation, expressed as percentages, as well as unvoiced sound and mode change percentages, have enabled us to distinguish among the pathologies selected for this study. The results obtained have helped us to make quantitative associations between cry characteristics and pathological conditions affecting newborns.
Cite this paper
Kheddache, Y. and Tadj, C. (2013) Acoustic measures of the cry characteristics of healthy newborns and newborns with pathologies. Journal of Biomedical Science and Engineering, 6, 796-804. doi: 10.4236/jbise.2013.68097.
Kheddache, Y. and Tadj, C. (2013) Acoustic measures of the cry characteristics of healthy newborns and newborns with pathologies. Journal of Biomedical Science and Engineering, 6, 796-804. doi: 10.4236/jbise.2013.68097.
References
[1] LaGasse, L.L., Neal, A.R. and Lester, B.M. (2005) Assessment of infant cry: Acoustic cry analysis and parental perception. Mental Retardation and Developmental Disabilities, 83-93. [2] Michelson, K., Todd de Barra, H. and Michelson, O. (2007) Sound spectrographic cry analysis and mothers perception of their infant’s crying. Nova Science Publishers, New York, 31-64. [3] Singer, L.T. and Zeskind, P.S. (2001) Biobehavioral assessment of the infant. In: Zeskind, P.S. and Lester, B.M., Eds., Analysis of Infant Crying. The Guilford Press, New York, 149-166. [4] Manfredi, C., D’Aniello, M. and Bruscaglioni, P. (1998) Acoustic measure of noise energy in patients having undergone a vocal fold operation. Proceedings of 9th European Signal Processing Conference, EUSIPCO 98, 2, 1141-1144,. [5] Wasz-Hockert, O., Michelsson, K. and Lind, J. (1985) Twenty-five years of Scandinavian cry research in infant crying: Theoretical and research perspectives. Lester, B.M. and Boukydis, C.F.Z., Eds., Plenum Press, New York, 83-104. [6] Kheddache, Y. and Tadj, C. (2013) Frequential characterization of healthy and pathological newborn cries. Submitted. [7] Frazier, R.H., Siamaksamsam, L., Braida, D. and Oppenheim, A.V. (1978) Enhancement of speech by adaptive filtering. Signal Processing, 4, 354. [8] Gerkmann, T. and Hendrik, R.C. (2012) Unbiased MMSE-based noise power estimation with low complexity and low tracking delay. IEEE Transactions on Audio, Speech, and Language Processing, 20, 1383-1393. doi:10.1109/TASL.2011.2180896 [9] Gerkmann, T. and Hendriks, R.C. (2011) Noise power estimation based on the probability of speech presence. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, 16-19 October 2011, 145-148. [10] Kasuya, H., Ogawa, S. and Kikuchi, Y. (1986) An adaptive comb filtering method as applied to acoustic analyses of pathological voice. ICASSP, Tokyo, 669-672. [11] Frazier, R.H. (1975) An adaptive filtering approach to speech enhancement. Massachusetts Institute of Technology. http://hdl.handle.net/10945/20716 [12] Hirschberg, J., Dejonckereb, P.H., Hiranoc, M., Moric, K., Schultz-Coulon, H.J. and Vrtickae, K. (1995) Voice disorders in children. International Journal of Pediatric Otorhinolaryngology, 32, 109-125. doi:10.1016/0165-5876(94)01149-R [13] Hirschberg, J. (1999) Dysphonia in infants. Elsevier Science, Ireland, 293-296. [14] Cecchini, M., Lai, C. and Langher, V. (2010) Dysphonic newborn cries allow prediction of their perceived meaning. Infant Behavior & Development, 33, 314-320. doi:10.1016/j.infbeh.2010.03.006 [15] Lester, B.M. and LaGasse, L.L. (2008) Crying. Elsevier, Amsterdam, 80-90. [16] Markel, J.D. (1972) The SIFT algorithm for fundamental frequency estimation. IEEE Transactions on Audio Electroacoustic, Au-20, 367-377. [17] Lederman, D. (2010) Estimation of infants’ cry fundamental frequency using a modified SIFT algorithm. arXiv:1009.2796. [18] Kasuya, H., Ogawa, S., Mashima, K. and Ebihara, S. (1986) Normalised noise measure to evaluate the pathological voice. Journal of the Acoustical Society of America, 1329-1334. doi:10.1121/1.394384 [19] Manfredi, C., Tocchioni, V. and Bocchi, L. (2006) A robust tool for newborn infant cry analysis. Proceedings of the 28th IEEE, 509-512. [20] Lim, J., Oppenhem, A.V. and Barida, L.D. (1978) Evaluation of an adaptive comb filtering method for enhancing speech degraded by white noise addition. IEEE ASSP, 26, 354-358. [21] Hendriks, R.C., Heusdens, R. and Jensen, J. (2010) MMSE-based noise PSD tracking with low complexity. ICASSP, 4266-4269.
[1] LaGasse, L.L., Neal, A.R. and Lester, B.M. (2005) Assessment of infant cry: Acoustic cry analysis and parental perception. Mental Retardation and Developmental Disabilities, 83-93. [2] Michelson, K., Todd de Barra, H. and Michelson, O. (2007) Sound spectrographic cry analysis and mothers perception of their infant’s crying. Nova Science Publishers, New York, 31-64. [3] Singer, L.T. and Zeskind, P.S. (2001) Biobehavioral assessment of the infant. In: Zeskind, P.S. and Lester, B.M., Eds., Analysis of Infant Crying. The Guilford Press, New York, 149-166. [4] Manfredi, C., D’Aniello, M. and Bruscaglioni, P. (1998) Acoustic measure of noise energy in patients having undergone a vocal fold operation. Proceedings of 9th European Signal Processing Conference, EUSIPCO 98, 2, 1141-1144,. [5] Wasz-Hockert, O., Michelsson, K. and Lind, J. (1985) Twenty-five years of Scandinavian cry research in infant crying: Theoretical and research perspectives. Lester, B.M. and Boukydis, C.F.Z., Eds., Plenum Press, New York, 83-104. [6] Kheddache, Y. and Tadj, C. (2013) Frequential characterization of healthy and pathological newborn cries. Submitted. [7] Frazier, R.H., Siamaksamsam, L., Braida, D. and Oppenheim, A.V. (1978) Enhancement of speech by adaptive filtering. Signal Processing, 4, 354. [8] Gerkmann, T. and Hendrik, R.C. (2012) Unbiased MMSE-based noise power estimation with low complexity and low tracking delay. IEEE Transactions on Audio, Speech, and Language Processing, 20, 1383-1393. doi:10.1109/TASL.2011.2180896 [9] Gerkmann, T. and Hendriks, R.C. (2011) Noise power estimation based on the probability of speech presence. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, 16-19 October 2011, 145-148. [10] Kasuya, H., Ogawa, S. and Kikuchi, Y. (1986) An adaptive comb filtering method as applied to acoustic analyses of pathological voice. ICASSP, Tokyo, 669-672. [11] Frazier, R.H. (1975) An adaptive filtering approach to speech enhancement. Massachusetts Institute of Technology. http://hdl.handle.net/10945/20716 [12] Hirschberg, J., Dejonckereb, P.H., Hiranoc, M., Moric, K., Schultz-Coulon, H.J. and Vrtickae, K. (1995) Voice disorders in children. International Journal of Pediatric Otorhinolaryngology, 32, 109-125. doi:10.1016/0165-5876(94)01149-R [13] Hirschberg, J. (1999) Dysphonia in infants. Elsevier Science, Ireland, 293-296. [14] Cecchini, M., Lai, C. and Langher, V. (2010) Dysphonic newborn cries allow prediction of their perceived meaning. Infant Behavior & Development, 33, 314-320. doi:10.1016/j.infbeh.2010.03.006 [15] Lester, B.M. and LaGasse, L.L. (2008) Crying. Elsevier, Amsterdam, 80-90. [16] Markel, J.D. (1972) The SIFT algorithm for fundamental frequency estimation. IEEE Transactions on Audio Electroacoustic, Au-20, 367-377. [17] Lederman, D. (2010) Estimation of infants’ cry fundamental frequency using a modified SIFT algorithm. arXiv:1009.2796. [18] Kasuya, H., Ogawa, S., Mashima, K. and Ebihara, S. (1986) Normalised noise measure to evaluate the pathological voice. Journal of the Acoustical Society of America, 1329-1334. doi:10.1121/1.394384 [19] Manfredi, C., Tocchioni, V. and Bocchi, L. (2006) A robust tool for newborn infant cry analysis. Proceedings of the 28th IEEE, 509-512. [20] Lim, J., Oppenhem, A.V. and Barida, L.D. (1978) Evaluation of an adaptive comb filtering method for enhancing speech degraded by white noise addition. IEEE ASSP, 26, 354-358. [21] Hendriks, R.C., Heusdens, R. and Jensen, J. (2010) MMSE-based noise PSD tracking with low complexity. ICASSP, 4266-4269.