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How effective is LENA in detecting speech vocalizations and language produced by children and adolescents with ASD in different contexts? / R. M. JONES in Autism Research, 12-4 (April 2019)
[article]
Titre : How effective is LENA in detecting speech vocalizations and language produced by children and adolescents with ASD in different contexts? Type de document : Texte imprimé et/ou numérique Auteurs : R. M. JONES, Auteur ; D. PLESA SKWERER, Auteur ; R. PAWAR, Auteur ; A. HAMO, Auteur ; Caroline CARBERRY, Auteur ; Eliana L. AJODAN, Auteur ; D. CAULLEY, Auteur ; M. R. SILVERMAN, Auteur ; S. MCADOO, Auteur ; S. MEYER, Auteur ; A. YODER, Auteur ; M. CLEMENTS, Auteur ; C. LORD, Auteur ; Helen TAGER-FLUSBERG, Auteur Article en page(s) : p.628-635 Langues : Anglais (eng) Mots-clés : Lena acoustic recordings autism spectrum disorder automated language detection communication Index. décimale : PER Périodiques Résumé : The LENA system was designed and validated to provide information about the language environment in children 0 to 4 years of age and its use has been expanded to populations with a number of communication profiles. Its utility in children 5 years of age and older is not yet known. The present study used acoustic data from two samples of children with autism spectrum disorders (ASD) to evaluate the reliability of LENA automated analyses for detecting speech utterances in older, school age children, and adolescents with ASD, in clinic and home environments. Participants between 5 and 18 years old who were minimally verbal (study 1) or had a range of verbal abilities (study 2) completed standardized assessments in the clinic (study 1 and 2) and in the home (study 2) while speech was recorded from a LENA device. We compared LENA segment labels with manual ground truth coding by human transcribers using two different methods. We found that the automated LENA algorithms were not successful (<50% reliable) in detecting vocalizations from older children and adolescents with ASD, and that the proportion of speaker misclassifications by the automated system increased significantly with the target-child's age. The findings in children and adolescents with ASD suggest possibly misleading results when expanding the use of LENA beyond the age ranges for which it was developed and highlight the need to develop novel automated methods that are more appropriate for older children. Autism Research 2019, 12: 628-635. (c) 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Current commercially available speech detection algorithms (LENA system) were previously validated in toddlers and children up to 48 months of age, and it is not known whether they are reliable in older children and adolescents. Our data suggest that LENA does not adequately capture speech in school age children and adolescents with autism and highlights the need to develop new automated methods for older children. En ligne : https://dx.doi.org/10.1002/aur.2071 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=389
in Autism Research > 12-4 (April 2019) . - p.628-635[article] How effective is LENA in detecting speech vocalizations and language produced by children and adolescents with ASD in different contexts? [Texte imprimé et/ou numérique] / R. M. JONES, Auteur ; D. PLESA SKWERER, Auteur ; R. PAWAR, Auteur ; A. HAMO, Auteur ; Caroline CARBERRY, Auteur ; Eliana L. AJODAN, Auteur ; D. CAULLEY, Auteur ; M. R. SILVERMAN, Auteur ; S. MCADOO, Auteur ; S. MEYER, Auteur ; A. YODER, Auteur ; M. CLEMENTS, Auteur ; C. LORD, Auteur ; Helen TAGER-FLUSBERG, Auteur . - p.628-635.
Langues : Anglais (eng)
in Autism Research > 12-4 (April 2019) . - p.628-635
Mots-clés : Lena acoustic recordings autism spectrum disorder automated language detection communication Index. décimale : PER Périodiques Résumé : The LENA system was designed and validated to provide information about the language environment in children 0 to 4 years of age and its use has been expanded to populations with a number of communication profiles. Its utility in children 5 years of age and older is not yet known. The present study used acoustic data from two samples of children with autism spectrum disorders (ASD) to evaluate the reliability of LENA automated analyses for detecting speech utterances in older, school age children, and adolescents with ASD, in clinic and home environments. Participants between 5 and 18 years old who were minimally verbal (study 1) or had a range of verbal abilities (study 2) completed standardized assessments in the clinic (study 1 and 2) and in the home (study 2) while speech was recorded from a LENA device. We compared LENA segment labels with manual ground truth coding by human transcribers using two different methods. We found that the automated LENA algorithms were not successful (<50% reliable) in detecting vocalizations from older children and adolescents with ASD, and that the proportion of speaker misclassifications by the automated system increased significantly with the target-child's age. The findings in children and adolescents with ASD suggest possibly misleading results when expanding the use of LENA beyond the age ranges for which it was developed and highlight the need to develop novel automated methods that are more appropriate for older children. Autism Research 2019, 12: 628-635. (c) 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Current commercially available speech detection algorithms (LENA system) were previously validated in toddlers and children up to 48 months of age, and it is not known whether they are reliable in older children and adolescents. Our data suggest that LENA does not adequately capture speech in school age children and adolescents with autism and highlights the need to develop new automated methods for older children. En ligne : https://dx.doi.org/10.1002/aur.2071 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=389 The stability and validity of automated vocal analysis in preverbal preschoolers with autism spectrum disorder / Tiffany G. WOYNAROSKI in Autism Research, 10-3 (March 2017)
[article]
Titre : The stability and validity of automated vocal analysis in preverbal preschoolers with autism spectrum disorder Type de document : Texte imprimé et/ou numérique Auteurs : Tiffany G. WOYNAROSKI, Auteur ; D. Kimbrough OLLER, Auteur ; Bahar KECELI-KAYSILI, Auteur ; Dongxin XU, Auteur ; Jeffrey A. RICHARDS, Auteur ; Jill GILKERSON, Auteur ; Sharmistha GRAY, Auteur ; Paul J. YODER, Auteur Article en page(s) : p.508-519 Langues : Anglais (eng) Mots-clés : useful speech language vocalizations automated vocal analysis LENA preschool preverbal autism Index. décimale : PER Périodiques Résumé : Theory and research suggest that vocal development predicts “useful speech” in preschoolers with autism spectrum disorder (ASD), but conventional methods for measurement of vocal development are costly and time consuming. This longitudinal correlational study examines the reliability and validity of several automated indices of vocalization development relative to an index derived from human coded, conventional communication samples in a sample of preverbal preschoolers with ASD. Automated indices of vocal development were derived using software that is presently “in development” and/or only available for research purposes and using commercially available Language ENvironment Analysis (LENA) software. Indices of vocal development that could be derived using the software available for research purposes: (a) were highly stable with a single day-long audio recording, (b) predicted future spoken vocabulary to a degree that was nonsignificantly different from the index derived from conventional communication samples, and (c) continued to predict future spoken vocabulary even after controlling for concurrent vocabulary in our sample. The score derived from standard LENA software was similarly stable, but was not significantly correlated with future spoken vocabulary. Findings suggest that automated vocal analysis is a valid and reliable alternative to time intensive and expensive conventional communication samples for measurement of vocal development of preverbal preschoolers with ASD in research and clinical practice. En ligne : http://dx.doi.org/10.1002/aur.1667 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=304
in Autism Research > 10-3 (March 2017) . - p.508-519[article] The stability and validity of automated vocal analysis in preverbal preschoolers with autism spectrum disorder [Texte imprimé et/ou numérique] / Tiffany G. WOYNAROSKI, Auteur ; D. Kimbrough OLLER, Auteur ; Bahar KECELI-KAYSILI, Auteur ; Dongxin XU, Auteur ; Jeffrey A. RICHARDS, Auteur ; Jill GILKERSON, Auteur ; Sharmistha GRAY, Auteur ; Paul J. YODER, Auteur . - p.508-519.
Langues : Anglais (eng)
in Autism Research > 10-3 (March 2017) . - p.508-519
Mots-clés : useful speech language vocalizations automated vocal analysis LENA preschool preverbal autism Index. décimale : PER Périodiques Résumé : Theory and research suggest that vocal development predicts “useful speech” in preschoolers with autism spectrum disorder (ASD), but conventional methods for measurement of vocal development are costly and time consuming. This longitudinal correlational study examines the reliability and validity of several automated indices of vocalization development relative to an index derived from human coded, conventional communication samples in a sample of preverbal preschoolers with ASD. Automated indices of vocal development were derived using software that is presently “in development” and/or only available for research purposes and using commercially available Language ENvironment Analysis (LENA) software. Indices of vocal development that could be derived using the software available for research purposes: (a) were highly stable with a single day-long audio recording, (b) predicted future spoken vocabulary to a degree that was nonsignificantly different from the index derived from conventional communication samples, and (c) continued to predict future spoken vocabulary even after controlling for concurrent vocabulary in our sample. The score derived from standard LENA software was similarly stable, but was not significantly correlated with future spoken vocabulary. Findings suggest that automated vocal analysis is a valid and reliable alternative to time intensive and expensive conventional communication samples for measurement of vocal development of preverbal preschoolers with ASD in research and clinical practice. En ligne : http://dx.doi.org/10.1002/aur.1667 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=304 A new measure of child vocal reciprocity in children with autism spectrum disorder / A. L. HARBISON in Autism Research, 11-6 (June 2018)
[article]
Titre : A new measure of child vocal reciprocity in children with autism spectrum disorder Type de document : Texte imprimé et/ou numérique Auteurs : A. L. HARBISON, Auteur ; Tiffany G. WOYNAROSKI, Auteur ; J. TAPP, Auteur ; J. W. WADE, Auteur ; A. S. WARLAUMONT, Auteur ; Paul J. YODER, Auteur Article en page(s) : p.903-915 Langues : Anglais (eng) Mots-clés : Lena autism automated vocal analysis preschool preverbal reciprocity vocalizations Index. décimale : PER Périodiques Résumé : Children's vocal development occurs in the context of reciprocal exchanges with a communication partner who models "speechlike" productions. We propose a new measure of child vocal reciprocity, which we define as the degree to which an adult vocal response increases the probability of an immediately following child vocal response. Vocal reciprocity is likely to be associated with the speechlikeness of vocal communication in young children with autism spectrum disorder (ASD). Two studies were conducted to test the utility of the new measure. The first used simulated vocal samples with randomly sequenced child and adult vocalizations to test the accuracy of the proposed index of child vocal reciprocity. The second was an empirical study of 21 children with ASD who were preverbal or in the early stages of language development. Daylong vocal samples collected in the natural environment were computer analyzed to derive the proposed index of child vocal reciprocity, which was highly stable when derived from two daylong vocal samples and was associated with speechlikeness of vocal communication. This association was significant even when controlling for chance probability of child vocalizations to adult vocal responses, probability of adult vocalizations, or probability of child vocalizations. A valid measure of children's vocal reciprocity might eventually improve our ability to predict which children are on track to develop useful speech and/or are most likely to respond to language intervention. A link to a free, publicly-available software program to derive the new measure of child vocal reciprocity is provided. Autism Res 2018, 11: 903-915. (c) 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Children and adults often engage in back-and-forth vocal exchanges. The extent to which they do so is believed to support children's early speech and language development. Two studies tested a new measure of child vocal reciprocity using computer-generated and real-life vocal samples of young children with autism collected in natural settings. The results provide initial evidence of accuracy, test-retest reliability, and validity of the new measure of child vocal reciprocity. A sound measure of children's vocal reciprocity might improve our ability to predict which children are on track to develop useful speech and/or are most likely to respond to language intervention. A free, publicly-available software program and manuals are provided. En ligne : http://dx.doi.org/10.1002/aur.1942 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=366
in Autism Research > 11-6 (June 2018) . - p.903-915[article] A new measure of child vocal reciprocity in children with autism spectrum disorder [Texte imprimé et/ou numérique] / A. L. HARBISON, Auteur ; Tiffany G. WOYNAROSKI, Auteur ; J. TAPP, Auteur ; J. W. WADE, Auteur ; A. S. WARLAUMONT, Auteur ; Paul J. YODER, Auteur . - p.903-915.
Langues : Anglais (eng)
in Autism Research > 11-6 (June 2018) . - p.903-915
Mots-clés : Lena autism automated vocal analysis preschool preverbal reciprocity vocalizations Index. décimale : PER Périodiques Résumé : Children's vocal development occurs in the context of reciprocal exchanges with a communication partner who models "speechlike" productions. We propose a new measure of child vocal reciprocity, which we define as the degree to which an adult vocal response increases the probability of an immediately following child vocal response. Vocal reciprocity is likely to be associated with the speechlikeness of vocal communication in young children with autism spectrum disorder (ASD). Two studies were conducted to test the utility of the new measure. The first used simulated vocal samples with randomly sequenced child and adult vocalizations to test the accuracy of the proposed index of child vocal reciprocity. The second was an empirical study of 21 children with ASD who were preverbal or in the early stages of language development. Daylong vocal samples collected in the natural environment were computer analyzed to derive the proposed index of child vocal reciprocity, which was highly stable when derived from two daylong vocal samples and was associated with speechlikeness of vocal communication. This association was significant even when controlling for chance probability of child vocalizations to adult vocal responses, probability of adult vocalizations, or probability of child vocalizations. A valid measure of children's vocal reciprocity might eventually improve our ability to predict which children are on track to develop useful speech and/or are most likely to respond to language intervention. A link to a free, publicly-available software program to derive the new measure of child vocal reciprocity is provided. Autism Res 2018, 11: 903-915. (c) 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Children and adults often engage in back-and-forth vocal exchanges. The extent to which they do so is believed to support children's early speech and language development. Two studies tested a new measure of child vocal reciprocity using computer-generated and real-life vocal samples of young children with autism collected in natural settings. The results provide initial evidence of accuracy, test-retest reliability, and validity of the new measure of child vocal reciprocity. A sound measure of children's vocal reciprocity might improve our ability to predict which children are on track to develop useful speech and/or are most likely to respond to language intervention. A free, publicly-available software program and manuals are provided. En ligne : http://dx.doi.org/10.1002/aur.1942 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=366