Comparison of Supervised-Learning Models and Auditory Discrimination of Infant Cries for the Early Detection of Developmental Disorders / Vergleich von Supervised-Learning Klassifikationsmodellen und menschlicher auditiver Diskriminationsfähigkeit zur Unterscheidung von Säuglingsschreien mit kongenitalen Entwicklungsstörungen

Tanja Fuhr; Henning Reetz; Carla Wegener

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Comparison of Supervised-Learning Models and Auditory Discrimination of Infant Cries for the Early Detection of Developmental Disorders / Vergleich von Supervised-Learning Klassifikationsmodellen und menschlicher auditiver Diskriminationsfähigkeit zur Unterscheidung von Säuglingsschreien mit kongenitalen Entwicklungsstörungen

Tanja Fuhr

Henning Reetz

Carla Wegener

| 30 janv. 2019

International Journal of Health Professions

Édition 6 (2019): Edition 1 (January 2019)

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Publié en ligne: 30 janv. 2019

Pages: 2 - 18

Reçu: 04 août 2018

Accepté: 26 oct. 2018

DOI: https://doi.org/10.2478/ijhp-2019-0003

Mots clés
Infant cry discrimination, cry classification, human listening, hearing experiment, auitory discrimnation skills

© 2019 Tanja Fuhr, Henning Reetz, Carla Wegener, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Overview of the training phase and rating phase for the human listeners and for the computational models. From the infant cry database in Setting B, the 18 cries used in the rating phase were excluded.

Pairwise contrasts of the real cry type groups

						95% Confidence Interval
Pairwise Contrasts	Contrast Estimate	Std. Error	t	df	Adj. Sig	Lower	Upper
HE - CLP	0,344	0,035	9,774	2150	0,000	0,241	0,447
HE - HI	0,162	0,037	4,442	2150	0,000	0,075	0,250
HE - BD	0,176	0,037	4,829	2150	0,000	0,080	0,273
HI - CLP	0,182	0,036	5,010	2150	0,000	0,084	0,279
HI - BD	0,014	0,038	0,376	2150	0,707	-0,060	0,088
LA- HE	0,212	0,031	6,860	2150	0,000	0,126	0,298
LA - CLP	0,556	0,031	18,231	2150	0,000	0,467	0,645
LA- HI	0,375	0,032	11,621	2150	0,000	0,282	0,467
LA- AS	0,132	0,029	4,516	2150	0,000	0,059	0,206
LA- BD	0,389	0,032	12,063	2150	0,000	0,297	0,480
AS - HE	0,080	0,034	2,337	2150	0,039	0,003	0,157
AS - CLP	0,424	0,034	12,516	2150	0,000	0,326	0,522
AS - HI	0,242	0,035	6,859	2150	0,000	0,144	0,340
AS - BD	0,256	0,035	7,261	2150	0,000	0,157	0,355
BD - CLP	0,168	0,036	4,622	2150	0,000	0,074	0,261

Confusion matrix of the ratings of the participants in the listening experiment

					Listener rating
		HE	CLP	HI	LA	AS	BD	Total
Real cry type	HE	230	48	55	2	10	15	360
	HE	63,9%	13,3%	15,3%	0,6%	2,8%	4,2%
	CLP	116	108	74	10	23	29	360
	CLP	32,2%	30,0%	20,6%	2,8%	6,4%	8,1%
	HI	49	73	172	12	9	45	360
	HI	13,6%	20,3%	47,8%	3,3%	2,5%	12,5%
	LA	4	12	22	308	3	11	360
	LA	1,1%	3,3%	6,1%	85,6%	0,8%	3,1%
	AS	4	29	14	6	259	48	360
	AS	1,1%	8,1%	3,9%	1,7%	71,9%	13,3%
	BD	31	58	30	13	61	167	360
	BD	8,6%	16,1%	8,3%	3,6%	16,9%	46,4%
	Total	434	328	367	351	365	315	2160

Pairwise contrasts of the RealCryType factor

						95% Confidence	Interval
Pairwise Contrasts	Contrast Estimate	Std. Error	t	df	Adj. Sig	Lower	Upper
HE - CLP	0,253	0,032	7,993	2475	0,000	0,163	0,343
HE - HI	0,108	0,027	3,947	2475	0,000	0,038	0,179
HE - BD	0,106	0,027	3,880	2475	0,000	0,038	0,174
HI - CLP	0,145	0,034	4,314	2475	0,000	0,056	0,234
HI - BD	-0,002	0,030	-0,071	2475	0,943	-0,061	0,057
LA - HE	0,116	0,021	5,510	2475	0,000	0,059	0,174
LA- CLP	0,370	0,032	11,420	2475	0,000	0,275	0,465
LA- HI	0,225	0,027	8,202	2475	0,000	0,145	0,304
LA- AS	0,069	0,018	3,832	2475	0,000	0,025	0,112
LA- BD	0,223	0,027	8,155	2475	0,000	0,144	0,301
AS - HE	0,048	0,022	2,185	2475	0,058	-0,001	0,097
AS - CLP	0,301	0,031	9,571	2475	0,000	0,209	0,393
AS - HI	0,156	0,027	5,810	2475	0,000	0,081	0,231
AS - BD	0,154	0,027	5,750	2475	0,000	0,080	0,228
BD - CLP	0,147	0,034	4,384	2475	0,000	0,057	0,237

Fixed effects impact on the rating correctness

Source	F	df1	df2	Sig
Corrected Model	30,056	9	2150	0,000
ListenerGroup	0,637	3	2150	0,591
RealCryType	53,099	5	2150	0,000
TestCries	7,078	1	2150	0,008

Random effect covariances

					95% Confidence Interval
Random Effect Covariance	Estimate	Std. Error	Z	Sig	Lower	Upper
RaterGroup * RaterID	0,098	0,045	2,197	0,028	0,040	0,240
RaterGroup * RaterID * RealCryType * TestCries	1,619E-19 This parameter is redundant.

Sensitivity and specificity values of the human listeners for identifying healthy infants

Listener group	Sensitivity	Specificity
Nurses	0,70	0,88
Naive listeners	0,59	0,89
Parents	0,69	0,89
Therapists	0,58	0,88
Total	0,64	0,89

Kappa statistics for the models of Settings A and B

Model Group	Kappa Value	Asymptotic Standard Error Not assuming the null hypothesis.	Approximate T Using the asymptotic standard error assuming the null hypothesis.
Models, Setting A	0,837	0,032	23,872
Models, Setting B	0,696	0,041	19,939
Total	0,527	0,012	58,796

Simple contrast of the known and unknown cries

						95% Confidence Interval
Simple Contrasts	Contrast Estimate	Std. Error	t	df	Adj. Sig	Lower	Upper
UKN cires - KN cries	-0,066	0,024	-2,692	2150	0,007	-0,113	-0,018

Simple contrast for the TestOrUnknownCry factor across all groups (KN=known cries, UKN=unknown cries).

						95% Confidence Interval
Simple Contrasts	Contrast Estimate	Std. Error	t	df	Adj. Sig	Lower	Upper
UKN KN cries cries -	-0,055	0,016	-3,433	2475	0,001	-0,087	-0,024

Correlation analysis to analyze the influence of the sociodemographic covariates on the rating correctness

		Age	No. children	Prof. experience	Correctness
Age	Correlation Coefficient Spearman’s rho	1,000	,633 Correlation is significant at the 0.01 level (2-tailed).	,599 Correlation is significant at the 0.01 level (2-tailed).	-0,024
Age	Sig. (2-tailed)		0,000	0,000	0,256
No. children	Correlation Coefficient Spearman’s rho	,633 Correlation is significant at the 0.01 level (2-tailed).	1,000	,205 Correlation is significant at the 0.01 level (2-tailed).	0,010
No. children	Sig. (2-tailed)	0,000		0,000	0,632
Prof. experience	Correlation Coefficient Spearman’s rho	,599 Correlation is significant at the 0.01 level (2-tailed).	,205 Correlation is significant at the 0.01 level (2-tailed).	1,000	0,019
Prof. experience	Sig. (2-tailed)	0,000	0,000		0,386
Correctness	Correlation Coefficient Spearman’s rho	-0,024	0,010	0,019	1,000
Correctness	Sig. (2-tailed)	0,256	0,632	0,386

Confusion matrix presenting the classifications of the supervised-learning models for the training Settings A and B compared to the actual cry types

			Rating
			HE	CLP	HI	LA	AS	BD	Total
Models, Setting A
	RealCryType
		HE	23	0	2	2	0	0	27
		HE	85,2%	0,0%	7,4%	7,4%	0,0%	0,0%	100,0%
		CLP	0	26	0	0	0	1	27
		CLP	0,0%	96,3%	0,0%	0,0%	0,0%	3,7%	100,0%
		HI	2	1	23	0	0	1	27
		HI	7,4%	3,7%	85,2%	0,0%	0,0%	3,7%	100,0%
		LA	1	0	0	26	0	0	27
		LA	3,7%	0,0%	0,0%	96,3%	0,0%	0,0%	100,0%
		AS	3	1	0	1	19	3	27
		AS	11,1%	3,7%	0,0%	3,7%	70,4%	11,1%	100,0%
		BD	2	1	1	0	0	23	27
		BD	7,4%	3,7%	3,7%	0,0%	0,0%	85,2%	100,0%
		Total	31	29	26	29	19	28	162
Models, Setting B
	RealCryType
		HE	18	5	4	0	0	0	27
		HE	66,7%	18,5%	14,8%	0,0%	0,0%	0,0%	100,0%
		CLP	4	21	2	0	0	0	27
		CLP	14,8%	77,8%	7,4%	0,0%	0,0%	0,0%	100,0%
		HI	3	4	20	0	0	0	27
		HI	11,1%	14,8%	74,1%	0,0%	0,0%	0,0%	100,0%
		LA	7	0	6	14	0	0	27
		LA	25,9%	0,0%	22,2%	51,9%	0,0%	0,0%	100,0%
		AS	1	1	1	1	22	1	27
		AS	3,7%	3,7%	3,7%	3,7%	81,5%	3,7%	100,0%
		BD	0	1	0	0	0	26	27
		BD	0,0%	3,7%	0,0%	0,0%	0,0%	96,3%	100,0%
		Total	33	32	33	15	22	27	162

Kappa statistics for the listener groups and for all listeners

Listener group	Kappa Value	Asymptotic Error Standardized Not assuming the null hypothesis.	Approximate T Using the asymptotic standard error assuming the null hypothesis.
Nurses	0,520	0,025	27,092
Naive listeners	0,498	0,025	25,884
Parents	0,471	0,026	24,514
Therapists	0,476	0,026	24,728
Total	0,491	0,013	51,095

Fixed effects impact on the rating correctness of computer models and human listeners

Source	F	df1	df2	Sig
Corrected Model	34,340	8	2475	0,000
RaterGroup	26,660	2	2475	0,000
RealCryType	45,894	5	2475	0,000
TestOrUnknownCry	11,497	1	2475	0,001

Pairwise contrasts of the RaterGroup factor

						95% Confidence Interval
Pairwise Contrasts	Contrast Estimate	Std. Error	t	df	Adj. Sig	Lower	Upper
Humans Setting - Models, A	-0,290	0,028	-10,179	2475	0,000	-0,358	-0,222
Humans Setting - Models, B	-0,181	0,039	-4,613	2475	8,331E-06	-0,269	-0,093
Models, Models, Setting Setting A B -	0,109	0,045	2,434	2475	0,015	0,021	0,196

Sensitivity and specificity values of the classification models for identifying healthy infants

Rater Group	Sensitivity	Specificity
Models, Setting A	0,85	0,94
Models, Setting B	0,67	0,90
Total	0,76	0,92

Sociodemographic parameters of the listener groups

Listener group	Naive listeners		Parents		Nurses/midwives		Therapists
(N = 120)	(N=30)		(N=30)		(N=30)		(N=30)
	Mean	SD	Mean	SD	Mean	SD	Mean	SD
Age [years]	23,3	2,6	31,4	5,4	32,4	6,4	35,5	7,1
No. Children			1,6	0,7	1,2	1,2	0,8	1,0
Prof. experience [years]					9,5	5,8	10,3	5,8

eISSN:: 2296-990X
Langues:: Anglais, Allemand

Périodicité:: Volume Open
Sujets de la revue:: Medicine, Clinical Medicine, other

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Publié en ligne: 30 janv. 2019

Pages: 2 - 18

Reçu: 04 août 2018

Accepté: 26 oct. 2018

DOI: https://doi.org/10.2478/ijhp-2019-0003

Mots clés
Infant cry discrimination, cry classification, human listening, hearing experiment, auitory discrimnation skills

© 2019 Tanja Fuhr, Henning Reetz, Carla Wegener, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Figure 1

Figure 2

Pairwise contrasts of the real cry type groups

Confusion matrix of the ratings of the participants in the listening experiment

Pairwise contrasts of the RealCryType factor

Fixed effects impact on the rating correctness

Random effect covariances

Sensitivity and specificity values of the human listeners for identifying healthy infants

Kappa statistics for the models of Settings A and B

Simple contrast of the known and unknown cries

Simple contrast for the TestOrUnknownCry factor across all groups (KN=known cries, UKN=unknown cries).

Correlation analysis to analyze the influence of the sociodemographic covariates on the rating correctness

Confusion matrix presenting the classifications of the supervised-learning models for the training Settings A and B compared to the actual cry types

Kappa statistics for the listener groups and for all listeners

Fixed effects impact on the rating correctness of computer models and human listeners

Pairwise contrasts of the RaterGroup factor

Sensitivity and specificity values of the classification models for identifying healthy infants

Sociodemographic parameters of the listener groups

Publié en ligne: 30 janv. 2019

Pages: 2 - 18

Reçu: 04 août 2018

Accepté: 26 oct. 2018

DOI: https://doi.org/10.2478/ijhp-2019-0003

Mots clésInfant cry discrimination, cry classification, human listening, hearing experiment, auitory discrimnation skills

© 2019 Tanja Fuhr, Henning Reetz, Carla Wegener, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Figure 1

Figure 2

Pairwise contrasts of the real cry type groups

Confusion matrix of the ratings of the participants in the listening experiment

Pairwise contrasts of the RealCryType factor

Fixed effects impact on the rating correctness

Random effect covariances

Sensitivity and specificity values of the human listeners for identifying healthy infants

Kappa statistics for the models of Settings A and B

Simple contrast of the known and unknown cries

Simple contrast for the TestOrUnknownCry factor across all groups (KN=known cries, UKN=unknown cries).

Correlation analysis to analyze the influence of the sociodemographic covariates on the rating correctness

Confusion matrix presenting the classifications of the supervised-learning models for the training Settings A and B compared to the actual cry types

Kappa statistics for the listener groups and for all listeners

Fixed effects impact on the rating correctness of computer models and human listeners

Pairwise contrasts of the RaterGroup factor

Sensitivity and specificity values of the classification models for identifying healthy infants

Sociodemographic parameters of the listener groups

Mots clés
Infant cry discrimination, cry classification, human listening, hearing experiment, auitory discrimnation skills