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Original Articles

Speech-driven mobile games for speech therapy: User experiences and feasibility

ORCID Icon, , , ORCID Icon, ORCID Icon & ORCID Icon
Pages 644-658 | Received 16 May 2017, Accepted 28 Jun 2018, Published online: 09 Oct 2018

References

  • American Speech-Language-Hearing Association. (2017). Apps for speech-language pathology and practice. Retrieved from http://www.asha.org/SLP/schools/Applications-for-Speech-Language-Pathology-Practice/
  • Balbus Speech. (2017). Speech4Good. [Mobile application software]. Retrieved from http://speech4good.com/features/
  • Bälter, O., Engwall, O., Öster, A.M., & Kjellström, H. (2005). Wizard-of-Oz test of ARTUR: A computer-based speech training system with articulation correction. Paper presented at the Proceedings of the 7th international ACM SIGACCESS conference on Computers and accessibility, Baltimore, MD, USA.
  • Expressive Solutions. (2018). ArtikPix (version 3.1.1). [Mobile application software]. Retrieved from http://expressive-solutions.com/artikpix/
  • Fitch, W.T., & Giedd, J. (1999). Morphology and development of the human vocal tract: A study using magnetic resonance imaging. The Journal of the Acoustical Society of America, 106, 1511–1522. doi:10.1121/1.427148
  • Ganzeboom, M., Yılmaz, E., Cucchiarini, C., & Strik, H. (2016). On the development of an ASR-based multimedia game for speech therapy: Preliminary results. In Proceedings of the 2016 ACM Workshop on Multimedia for Personal Health and Health Care. (pp. 3–8). ACM. Retrieved from https://dl.acm.org/citation.cfm?id=2985771
  • Goldwater, S., Jurafsky, D., & Manning, C.D. (2010). Which words are hard to recognize? Prosodic, lexical, and disfluency factors that increase speech recognition error rates. Speech Communication, 52, 181–200. doi:10.1016/j.specom.2009.10.001
  • IdeaMK. (2017). Whack A Mole (version 1.8). [Mobile application software]. Retrieved from https://play.google.com/store/apps
  • Jamieson, D.G., Kranjc, G., Yu, K., & Hodgetts, W.E. (2004). Speech intelligibility of young school-aged children in the presence of real-life classroom noise. Journal of the American Academy of Audiology, 15, 508–517. doi:10.3766/jaaa.15.7.5
  • Kennedy, J., Lemaignan, S., Montassier, C., Lavalade, P., Irfan, B., Papadopoulos, F., … Belpaeme, T. (2017). Child speech recognition in human-robot interaction: evaluations and recommendations. InProceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction (pp. 82–90).ACM. Retrieved from https://dl.acm.org/citation.cfm?id=3020229
  • Lan, T., Aryal, S., Ahmed, B., Ballard, K., & Gutierrez-Osuna, R. (2014). Flappy voice: An interactive game for childhood apraxia of speech therapy. Paper presented at the Proceedings of the first ACM SIGCHI annual symposium on Computer-human interaction in play. Retrieved from https://dl.acm.org/citation.cfm?id=2661305
  • Laureate Learning Systems. (2014). TalkTime with Tucker. [Mobile application software]. Retrieved from http://www.laureatelearning.com/products/descriptions/talktdesc.html
  • Lee, S., Potamianos, A., & Narayanan, S. (1999). Acoustics of children’s speech: Developmental changes of temporal and spectral parameters. The Journal of the Acoustical Society of America, 105, 1455–1468. doi:10.1121/1.426686
  • Little Bee Speech. (2018). b Station app for iPad & iPhone. [Mobile application software]. Retrieved from http://littlebeespeech.com/apps.php
  • Lopes, M., Magalhães, J., & Cavaco, S. (2016). A voice-controlled serious game for the sustained vowel exercise. In Proceedings of the 13th International Conference on Advances in Computer Entertainment Technology (p. 32). ACM. Retrieved from https://dl.acm.org/citation.cfm?id=3001807
  • Luce, P.A., & Pisoni, D.B. (1998). Recognizing spoken words: The neighborhood activation model. Ear and Hearing, 19, 1–36. doi:10.1097/00003446-199802000-00001
  • Maas, E., Robin, D.A., Hula, S.N.A., Freedman, S.E., Wulf, G., Ballard, K.J., & Schmidt, R.A. (2008). Principles of motor learning in treatment of motor speech disorders. American Journal of Speech-Language Pathology, 17, 277–298. doi:10.1044/1058-0360(2008/025)
  • Micro Video Corporation. (2014). Video Voice. [Mobile application software]. Retrieved from http://www.videovoice.com/default.htm
  • Minimal Games. (2018). Asteroids (version 1.7). [Mobile application software]. Retrieved from https://play.google.com/store/apps
  • Mostow, J., & Aist, G. (2001). Evaluating tutors that listen: An overview of Project LISTEN. In K.D. Forbus & P.J. Feltovich (Eds.), Smart machines in education (pp. 169–234). Cambridge, MA: AAAI Press/The MIT Press.
  • Murray, E., McCabe, P., & Ballard, K.J. (2014). A systematic review of treatment outcomes for children with childhood apraxia of speech. American Journal of Speech-Language Pathology, 23, 486–504. DOI: doi:10.1044/2014_AJSLP-13-0035
  • NDP3. (2017). Nuffield Dyspraxia Programme. Retrived from https://www.ndp3.org/
  • Newell, K., Carlton, M., & Antoniou, A. (1990). The interaction of criterion and feedback information in learning a drawing task. Journal of Motor Behavior, 22, 536–552. doi:10.1080/00222895.1990.10735527
  • Parnandi, A., Karappa, V., Lan, T., Shahin, M., McKechnie, J., Ballard, K., … Gutierrez-Osuna, R. (2015). Development of a remote therapy tool for childhood apraxia of speech. ACM Transactions on Accessible Computing (TACCESS), 7, 1–23. doi:10.1145/2776895
  • Poulsen, R., Hastings, P., & Allbritton, D. (2007). Tutoring bilingual students with an automated Reading Tutor that listens. Journal of Educational Computing Research, 36, 191–221. doi:10.2190/A007-367T-5474-8383
  • Pratt, S.R., Heintzelman, A.T., & Deming, S.E. (1993). The efficacy of using the IBM speech viewer vowel accuracy module to treat young children with hearing impairment. Journal of Speech and Hearing Research, 36, 1063–1074. doi:10.1044/jshr.3605.1063
  • Rubin, Z., & Kurniawan, S. (2013). Speech adventure: Using speech recognition for cleft speech therapy. In Proceedings of the 6th International Conference on Pervasive Technologies Related to Assistive Environments. (p. 35). ACM. Retrieved from https://dl.acm.org/citation.cfm?id=2504373
  • Ruggero, L., McCabe, P., Ballard, K., & Munro, N. (2012). Paediatric speech-language pathology service delivery: An exploratory survey of Australian parents. International Journal of Speech-Language Pathology, 14, 338–350.
  • Shivakumar, P.G., Potamianos, A., Lee, S., & Narayanan, S. (2014). Improving speech recognition for children using acoustic adaptation and pronunciation modeling. In WOCCI (pp. 15–19). Retrieved from https://www.isca-speech.org/archive/wocci_2014/wc14_015.html
  • Shriberg, L.D., & Kwiatkowski, J. (1982). Phonological disorders III: A procedure for assessing severity of involvement. Journal of Speech, Language, and Hearing Research, 47, 256–270.
  • Smarty Ears. (2017). Apraxiaville. [Mobile application software]. Retrieved from http://smartyearsapps.com/service/apraxia-ville/
  • Smarty Ears. (2017). Articulate it. [Mobile application software]. Retrieved from http://smartyearsapps.com/service/articulate-it/
  • SourceForge. (2018). CMU PocketSphinx. [Mobile application software]. Retrieved from http://sourceforge.net/projects/cmusphinx/
  • Speech With Milo. (2017). Speech with Milo – Apps for speech therapy. [Mobile application software]. Retrieved from http://www.speechwithmilo.com/
  • Squadventure. (2018). Word Pop: Endless brain game. [Mobile application software]. Retrieved from http://itunes.apple.com
  • Tactus Therapy Solutions. Speech Flipbook. [Mobile application software]. Retrieved from http://tactustherapy.com/apps/speechflipbook/
  • Tan, C.T., Johnston, A., Ferguson, S., Ballard, K., & Bluff, A. (2014). Retrogaming as visual feedback for speech therapy. Paper presented at the in Proceedings of SIGGRAPH Asia 2014 MGIA, New York.
  • Tiga, T. (2011). Tiga talk speech therapy games. [Mobile application software]. Retrieved from http://tigatalk.com/app/
  • Xu, D., Richards, J.A., & Gilkerson, J. (2014). Automated analysis of child phonetic production using naturalistic recordings. Journal of Speech, Language, and Hearing Research, 57, 1638–1650. doi:10.1044/2014_JSLHR-S-13-0037

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