PDF herunterladen
Semin Speech Lang 2016; 37(02): 128-142
DOI: 10.1055/s-0036-1580745
Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

HomeBank: An Online Repository of Daylong Child-Centered Audio Recordings

Mark VanDam
1   Department of Speech and Hearing Sciences, Elson S. Floyd College of Medicine, Washington State University, and Spokane Hearing Oral Program of Excellence (HOPE), Spokane, Washington
,
Anne S. Warlaumont
2   Cognitive and Information Sciences, University of California, Merced, California
,
Elika Bergelson
3   Department of Brain and Cognitive Sciences, University of Rochester, Rochester, New York
,
Alejandrina Cristia
4   Laboratoire de Sciences Cognitives et Psycholinguistique (ENS, EHESS, CNRS), Département d'Etudes Cognitives, Ecole Normale Supérieure, PSL Research University, Paris, France
,
Melanie Soderstrom
5   Department of Psychology, University of Manitoba, Winnipeg, MB, Canada
,
Paul De Palma
6   Department of Computer Science, School of Engineering and Applied Science, Gonzaga University, Spokane, Washington
,
Brian MacWhinney
7   Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania
› Institutsangaben
Weitere Informationen

Publikationsverlauf

Publikationsdatum:
25. April 2016 (online)

Auch verfügbar auf
   Lizenzen und Reprints

Abstract

HomeBank is introduced here. It is a public, permanent, extensible, online database of daylong audio recorded in naturalistic environments. HomeBank serves two primary purposes. First, it is a repository for raw audio and associated files: one database requires special permissions, and another redacted database allows unrestricted public access. Associated files include metadata such as participant demographics and clinical diagnostics, automated annotations, and human-generated transcriptions and annotations. Many recordings use the child-perspective LENA recorders (LENA Research Foundation, Boulder, Colorado, United States), but various recordings and metadata can be accommodated. The HomeBank database can have both vetted and unvetted recordings, with different levels of accessibility. Additionally, HomeBank is an open repository for processing and analysis tools for HomeBank or similar data sets. HomeBank is flexible for users and contributors, making primary data available to researchers, especially those in child development, linguistics, and audio engineering. HomeBank facilitates researchers' access to large-scale data and tools, linking the acoustic, auditory, and linguistic characteristics of children's environments with a variety of variables including socioeconomic status, family characteristics, language trajectories, and disorders. Automated processing applied to daylong home audio recordings is now becoming widely used in early intervention initiatives, helping parents to provide richer speech input to at-risk children.

Keywords

Databases - speech production - automatic speech recognition - language acquisition - child language
 

  • References

  • 1 Lynip AW. The use of magnetic devices in the collection and analysis of the preverbal utterances of an infant. Genet Psychol Monogr 1951; 44 (2) 221-262
    PubMedGoogle Scholar
  • 2 Chomsky N. A review of BF Skinner's Verbal Behavior. Language 1959; 35 (1) 26-58
    CrossrefPubMedGoogle Scholar
  • 3 Skinner BF. Verbal Behavior. New York, NY: Appleton-Century-Crofts; 1957
    CrossrefGoogle Scholar
  • 4 Oller DK. The Emergence of the Speech Capacity. Mahwah, NJ: Lawrence Erlbaum Associates; 2000
    Google Scholar
  • 5 Brown R. A First Language: The Early Stages. Cambridge, MA: Harvard University Press; 1973
    CrossrefGoogle Scholar
  • 6 Lenneberg EH, Chomsky N, Marx O. Biological Foundations of Language. New York, NY: Wiley; 1967
    Google Scholar
  • 7 Oller DK, Wieman LA, Doyle WJ, Ross C. Infant babbling and speech. J Child Lang 1976; 3: 1-11
    PubMedGoogle Scholar
  • 8 Snow CE, Ferguson CA. Talking to Children: Language Input and Acquisition. Cambridge, UK: Cambridge University Press; 1977
    Google Scholar
  • 9 Korman M. Adaptive aspects of maternal vocalizations in differing contexts at ten weeks. First Lang 1984; 5: 44-45
    PubMedGoogle Scholar
  • 10 MacWhinney B. The CHILDES Project: The Database. Vol. 2. New York, NY: Psychology Press; 2000
    Google Scholar
  • 11 Harkness S. Cultural variation in mothers' language. Word 1975; 27: 495-498
    PubMedGoogle Scholar
  • 12 Harkness S. Aspects of social environment and first language acquisition in rural Africa. In: Snow CE, Ferguson CA, eds. Talking to Children: Language Input and Acquisition. Cambridge, UK: Cambridge University Press; 1977: 309
    Google Scholar
  • 13 Wells G. Describing children's linguistic development at home and at school. Br Educ Res J 1979; 5 (1) 75-98
    CrossrefPubMedGoogle Scholar
  • 14 Hart B, Risley TR. Meaningful Differences in the Everyday Experience of Young American Children. Baltimore, MD: Paul H. Brookes Publishing; 1995
    Google Scholar
  • 15 Hart B, Risley T. The early catastrophe. Am Educ 2003; 27 (4) 6-9
    PubMedGoogle Scholar
  • 16 Roy BC, Roy D. Fast transcription of unstructured audio recordings. Paper presented at: Proceedings of the 10th Annual Conference of the International Communication Association INTERSPEECH 2009; September 6–10, 2009; Brighton, UK
    PubMedGoogle Scholar
  • 17 Roy BC, Frank MC, Roy D. Relating activity contexts to early word learning in dense longitudinal data. Paper presented at: Proceedings of the 34th Annual Cognitive Science Conference; August 1–4, 2012; Sapporo, Japan
    PubMedGoogle Scholar
  • 18 Roy BC, Frank MC, DeCamp P, Miller M, Roy D. Predicting the birth of a spoken word. Proc Natl Acad Sci U S A 2015; 112 (41) 12663-12668
    CrossrefPubMedGoogle Scholar
  • 19 Dykstra JR, Sabatos-Devito MG, Irvin DW, Boyd BA, Hume KA, Odom SL. Using the Language Environment Analysis (LENA) system in preschool classrooms with children with autism spectrum disorders. Autism 2013; 17 (5) 582-594
    CrossrefPubMedGoogle Scholar
  • 20 Oller DK, Niyogi P, Gray S , et al. Automated vocal analysis of naturalistic recordings from children with autism, language delay, and typical development. Proc Natl Acad Sci U S A 2010; 107 (30) 13354-13359
    CrossrefPubMedGoogle Scholar
  • 21 Warlaumont AS, Richards JA, Gilkerson J, Oller DK. A social feedback loop for speech development and its reduction in autism. Psychol Sci 2014; 25 (7) 1314-1324
    CrossrefPubMedGoogle Scholar
  • 22 Warren SF, Gilkerson J, Richards JA , et al. What automated vocal analysis reveals about the vocal production and language learning environment of young children with autism. J Autism Dev Disord 2010; 40 (5) 555-569
    CrossrefPubMedGoogle Scholar
  • 23 VanDam M, Oller DK, Ambrose SE , et al. Automated vocal analysis of children with hearing loss and their typical and atypical peers. Ear Hear 2015; 36 (4) e146-e152
    CrossrefPubMedGoogle Scholar
  • 24 VanDam M, Moeller MP, Tomblin JB. Analyses of fundamental frequency in infants and preschoolers with hearing loss. Paper presented at: 160th Meeting of the Acoustical Society of America; November 18, 2010; Cancun, Mexico
    PubMedGoogle Scholar
  • 25 Caskey M, Stephens B, Tucker R, Vohr B. Importance of parent talk on the development of preterm infant vocalizations. Pediatrics 2011; 128 (5) 910-916
    CrossrefPubMedGoogle Scholar
  • 26 Johnson K, Caskey M, Rand K, Tucker R, Vohr B. Gender differences in adult-infant communication in the first months of life. Pediatrics 2014; 134 (6) e1603-e1610
    CrossrefPubMedGoogle Scholar
  • 27 Ambrose SE, VanDam M, Moeller MP. Linguistic input, electronic media, and communication outcomes of toddlers with hearing loss. Ear Hear 2014; 35 (2) 139-147
    CrossrefPubMedGoogle Scholar
  • 28 Aragon M, Yoshinaga-Itano C. Using Language ENvironment Analysis to improve outcomes for children who are deaf or hard of hearing. Semin Speech Lang 2012; 33 (4) 340-353
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 29 Christakis DA, Gilkerson J, Richards JA , et al. Audible television and decreased adult words, infant vocalizations, and conversational turns: a population-based study. Arch Pediatr Adolesc Med 2009; 163 (6) 554-558
    CrossrefPubMedGoogle Scholar
  • 30 Zimmerman FJ, Gilkerson J, Richards JA , et al. Teaching by listening: the importance of adult-child conversations to language development. Pediatrics 2009; 124 (1) 342-349
    CrossrefPubMedGoogle Scholar
  • 31 Hodson H. Automatic voice coach gives conversation tips to parents. New Sci 2014; 221 (2954) 22
    PubMedGoogle Scholar
  • 32 Suskind DL, Graf E, Leffel KR , et al. Project ASPIRE: Spokane language intervention curriculum for parents of low socio-economic status and their deaf and hard-of-hearing children. Otol Neurotol 2016; 37 (2) e110-e117
    CrossrefPubMedGoogle Scholar
  • 33 Sacks C, Shay S, Repplinger L , et al. Pilot testing of a parentdirected intervention (project ASPIRE) for undeserved children who are deaf or hard of hearing. Child Lang Teach Ther 2014; 30: 91-102
    CrossrefPubMedGoogle Scholar
  • 34 Leffel K, Suskind D. Parent-directed approaches to enrich the early language environments of children living in poverty. Semin Speech Lang 2013; 34 (4) 267-278
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 35 Ford M, Baer CT, Xu D, Yapanel U, Gray S. The LENA language environment analysis system: audio specifications of the DLP-0121. LENA Foundation Technical Report LTR-03–2. 2008; Available at: http://www.lenafoundation.org/wp-content/uploads/2014/10/LTR-03-2_Audio_Specifications.pdf . Accessed January 25, 2016
    PubMedGoogle Scholar
  • 36 VanDam M. Acoustic characteristics of the clothes used for a wearable recording device. J Acoust Soc Am 2014; 136 (4) EL263-EL267
    CrossrefPubMedGoogle Scholar
  • 37 Xu D, Yapanel U, Gray S, Baer CT. The LENA™ Language Environment Analysis System: the interpretive time segments (ITS) file. LENA Foundation Technical Report No. LTR-04–2. 2008; Available at: https://www.lenafoundation.org/wp-content/uploads/2014/10/LTR-04-2_ITS_File.pdf . Accessed March 18, 2016
    PubMedGoogle Scholar
  • 38 Oller DK. LENA: automated analysis algorithms and segmentation detail: how to interpret and not overinterpret the LENA labelings. Paper presented at: LENA Users Conference; April 2011; Denver, CO
    PubMedGoogle Scholar
  • 39 Gilkerson J, Richards JA. Impact of adult talk, conversational turns, and TV during the critical 0–4 years of child development. Technical Report LTR-01-2. 2008. Available at: https://www.lenafoundation.org/wp-content/uploads/2014/10/LTR-01-2_PowerOfTalk.pdf . Accessed September 6, 2010
    PubMedGoogle Scholar
  • 40 Richards JA, Gilkerson J, Paul T, Xu D. The LENA automatic vocalization assessment. Technical Report LTR-08–1. 2008. Available at: http://www.lenafoundation.org/wp-content/uploads/2014/10/LTR-08-1_Automatic_Vocalization_Assessment.pdf . Accessed January 25, 2016
    PubMedGoogle Scholar
  • 41 Xu D, Yapanel UH, Gray S, Gilkerson J, Richards JA, Hansen JH. Signal processing for young child speech language development. Paper presented at: First Workshop on Child, Computer and Interaction WOCCI; October 23, 2008; Chania, Crete
    PubMedGoogle Scholar
  • 42 Xu D, Richards JA, Gilkerson J, Yapanel U, Gray S, Hanson J. Automatic childhood autism detection by vocalization decomposition with phone-like units. Paper presented at: Second Workshop on Child, Computer and Interaction WOCCI; November 5, 2009; Cambridge, MA
    PubMedGoogle Scholar
  • 43 Xu D, Richards JA, Gilkerson J. Automated analysis of child phonetic production using naturalistic recordings. J Speech Lang Hear Res 2014; 57 (5) 1638-1650
    CrossrefPubMedGoogle Scholar
  • 44 Bořil H, Zhang Q, Ziaei A , et al. Automatic assessment of language background in toddlers through phonotactic and pitch pattern modeling of short vocalizations. Paper presented at: Fourth Workshop on Child Computer Interaction WOCCI; Available at: http://www.utd.edu/∼hynek/pdfs/WOCCI14.pdf . Accessed January 25, 2016
    PubMedGoogle Scholar
  • 45 Xu D, Paul TD. System and method for expressive language and developmental disorder assessment. U.S. Patent US8938390B2; January 20, 2015
    PubMedGoogle Scholar
  • 46 Bořil H, Hansen JH. UT-Scope: towards LVCSR under Lombard effect induced by varying types and levels of noisy background. Paper presented at: Acoustics, Speech and Signal Processing (ICASSP) 2011 IEEE International Conference; May 22, 2011; Prague, Czech Republic
    PubMedGoogle Scholar
  • 47 VanDam M, De Palma P. Fundamental frequency of child-directed speech using automatic speech recognition. Paper presented at: IEEE Proceedings of the Joint 7th International Conference on Soft Computing and Intelligent Systems and 15th International Symposium on Advanced Intelligent Systems; December 10, 2014; Kitakyushu, Japan
    PubMedGoogle Scholar
  • 48 Soderstrom M, Wittebolle K. When do caregivers talk? The influences of activity and time of day on caregiver speech and child vocalizations in two childcare environments. PLoS ONE 2013; 8 (11) e80646
    CrossrefPubMedGoogle Scholar
  • 49 VanDam M, Silbert NH. Precision and error of automatic speech recognition. Proceedings of Meetings on Acoustics 2013; 19: 060006
    PubMedGoogle Scholar
  • 50 Weisleder A, Fernald A. Talking to children matters: early language experience strengthens processing and builds vocabulary. Psychol Sci 2013; 24 (11) 2143-2152
    CrossrefPubMedGoogle Scholar
  • 51 Berends C. The LENA System in Parent-Child Interaction in Dutch Preschool Children with Language Delay [M.A. thesis]. Utrecht, Holland: UMC-Utrecht; 2015
    PubMedGoogle Scholar
  • 52 Canault M, Le Normand MT, Foudil S, Loundon N, Thai-Van H. Reliability of the Language ENvironment Analysis system (LENA™) in European French. Behav Res Methods 2015; 15: 1-6
    PubMedGoogle Scholar
  • 53 MacWhinney B. The CHILDES Project: Tools for Analyzing Talk, 3rd ed. Mahwah, NJ: Lawrence Erlbaum Associates; 2000
    Google Scholar
  • 54 Adolph KE, Gilmore RO, Freeman C, Sanderson P, Millman D. Toward open behavioral science. Psychol Inq 2012; 23 (3) 244-247
    CrossrefPubMedGoogle Scholar
  • 55 MacWhinney B. The TalkBank Project. In: Beal JC, Corrigan KP, Moisl HL, eds. Creating and Digitizing Language Corpora: Synchronic Databases. Vol. 1; Houndmills: Palgrave-Macmillan; 2007: 163-180
    CrossrefGoogle Scholar
  • 56 Rose Y, MacWhinney B, Byrne R , et al. Introducing Phon: a software solution for the study of phonological acquisition. In: Proceedings of the 30th Annual Boston University Conference on Language Development. Somerville, MA: Cascadilla Press; 2006:489–500
    PubMedGoogle Scholar
  • 57 Boersma P, Weenink D. Praat: doing phonetics by computer [computer program]. Available at: http://www.fon.hum.uva.nl/praat/ . Accessed January 25, 2015
    PubMedGoogle Scholar
  • 58 Boersma P. The use of Praat in corpus research. Available at: http://fonsg3.hum.uva.nl/paul/papers/PraatForCorpora2.pdf . Accessed January 25, 2016
    PubMedGoogle Scholar
  • 59 U.S. Department of Health and Human Services. The Belmont Report: ethical principles and guidelines for the protection of human subjects of research. 1979. Available at: hhs.gov/ohrp/humansubjects/guidance/belmont.html . Accessed January 25, 2015
    PubMedGoogle Scholar
  • 60 Hinton G, Deng L, Yu D , et al. Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups. Signal Processing Magazine 2012; 29 (6) 82-97
    PubMedGoogle Scholar
  • 61 Fernald A, Taeschner T, Dunn J, Papousek M, de Boysson-Bardies B, Fukui I. A cross-language study of prosodic modifications in mothers' and fathers' speech to preverbal infants. J Child Lang 1989; 16 (3) 477-501
    CrossrefPubMedGoogle Scholar
  • 62 Hoff-Ginsberg E. Some contributions of mothers' speech to their children's syntactic growth. J Child Lang 1985; 12 (2) 367-385
    PubMedGoogle Scholar
  • 63 Mannle S, Tomasello M. Fathers, siblings, and the bridge hypothesis. Children's Language 1987; 6: 23-42
    PubMedGoogle Scholar
  • 64 Reese E, Fivush R. Parental styles of talking about the past. Dev Psychol 1993; 29 (3) 596-606
    CrossrefPubMedGoogle Scholar
  • 65 Tenenbaum HR, Leaper C. Mothers' and fathers' questions to their child in Mexican-descent families: moderators of cognitive demand during play. Hisp J Behav Sci 1997; 19 (3) 318-332
    CrossrefPubMedGoogle Scholar
  • 66 Tenenbaum HR, Leaper C. Gender effects on Mexican-descent parents' questions and scaffolding during toy play: a sequential analysis. First Lang 1998; 18 (53) 129-147
    CrossrefPubMedGoogle Scholar
  • 67 Tenenbaum HR, Leaper C. Parent-child conversations about science: the socialization of gender inequities?. Dev Psychol 2003; 39 (1) 34-47
    CrossrefPubMedGoogle Scholar
  • 68 VanDam M, Strong W, De Palma P. Characteristics of fathers' prosody when talking with young children. Paper presented at: American Speech-Language Hearing Association (ASHA) Convention; November 12, 2015; Denver, CO
    PubMedGoogle Scholar
  • 69 VanDam M, De Palma P, Strong WE. Fathers' use of fundamental frequency in motherese. Poster presented at: 169th Meeting of the Acoustical Society of America; May 2015; Pittsburgh, PA
    PubMedGoogle Scholar
  • 70 VanDam M, De Palma P, Strong WE, Kelly E. Child-directed speech of fathers. Poster presented at: Linguistic Society of America 2015 Annual Meeting; January 10, 2015; Portland, OR
    PubMedGoogle Scholar
  • 71 Ko ES, Seidl A, Cristia A, Reimchen M, Soderstrom M. Entrainment of prosody in the interaction of mothers with their young children. J Child Lang 2016; 43 (2) 284-309
    CrossrefPubMedGoogle Scholar
  • 72 Warlaumont AS, Oller DK, Dale R, Richards JA, Gilkerson J, Xu D. Vocal interaction dynamics of children with and without autism. In: Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society, 2010:121–126
    PubMedGoogle Scholar
  • 73 Abney DH, Warlaumont AS, Haussman A, Ross JM, Wallot S. Using nonlinear methods to quantify changes in infant limb movements and vocalizations. Front Psychol 2014; 5: 771
    PubMedGoogle Scholar
  • 74 Karmiloff-Smith A. Development itself is the key to understanding developmental disorders. Trends Cogn Sci 1998; 2 (10) 389-398
    CrossrefPubMedGoogle Scholar
  • 75 Leezenbaum NB, Campbell SB, Butler D, Iverson JM. Maternal verbal responses to communication of infants at low and heightened risk of autism. Autism 2014; 18 (6) 694-703
    CrossrefPubMedGoogle Scholar