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Tara McAllister

Associate Professor; Director, Doctoral Program

Communicative Sciences and Disorders


Tara McAllister is a linguist and speech-language pathologist who studies speech learning in various populations, notably children with speech sound disorder. Her research aims to understand how articulatory and perceptual factors shape speech learning outcomes, and why developmental speech patterns resolve in some individuals but persist in others. As director of the Biofeedback Intervention Technology for Speech (BITS) Lab at NYU, she has conducted multiple studies measuring the efficacy of acoustic and ultrasound biofeedback in the treatment of persistent speech sound deviations. BITS lab research is funded by the NIH National Institute on Deafness and Other Communication Disorders. Since 2014, Dr. McAllister has directed the development of staRt, an iOS app to make biofeedback speech training more widely accessible. She earned an A.B./A.M. in linguistics from Harvard University, an M.S. in communication disorders from Boston University, and a Ph.D. in linguistics from MIT.

Link to academic website

Selected Publications

  • McAllister, T., Nightingale, C., Moya-Gale, G., Kawamura, A., & Ramig, L. O. (2023). Crowdsourced perceptual ratings of voice quality in people with Parkinson’s Disease before and after intensive voice and articulation therapies: Secondary outcome of a randomized controlled trial. Journal of Speech, Language, and Hearing Research, 66(5), 1541-1562. DOI: 10.1044/2023_JSLHR-22-00694 Link to preprint and code
  • Benway, N. R., Preston, J. L., Hitchcock, E. R., Rose, Y., Salekin, A., Liang, W., & McAllister, T. (2023). Reproducible speech research with the artificial-intelligence-ready PERCEPT corpora. Journal of Speech, Language, and Hearing Research, 66(6), 1986-2009. DOI: 10.1044/2023_JSLHR-22-00343 Link to postprint manuscript
  • Hitchcock, E. R., Ochs, L. C., Swartz, M. T., Leece, M. C., Preston, J. L., & McAllister, T. (2023). Tutorial: Using visual-acoustic biofeedback for speech sound training. American Journal of Speech-Language Pathology, 32(1), 18-36. Link to postprint manuscript
  • Ayala, S.A., Eads, A., Kabakoff, H., Swartz, M., Shiller, D.M., Hill, J., Hitchcock, E.R., Preston, J.L., & McAllister, T. (2023). Auditory and somatosensory development for speech in later childhood. Journal of Speech, Language, and Hearing Research, 66(4), 1252-1273. Link to postprint and code
  • Canta, A.J., Abu El Adas, S., Washington, K.N., & McAllister, T. (2023). Variability, accuracy, and cross-linguistic transfer in bilingual children speaking Jamaican Creole and English. Clinical Linguistics & Phonetics, 37(4-6), 436-453. DOI: 10.1080/02699206.2022.2074311
  • Kabakoff, H., Beames, S.P., Tiede, M., Whalen, D.H., Preston, J.L., & McAllister, T. (2023). Comparing metrics for quantification of children’s tongue shape complexity using ultrasound imaging. Clinical Linguistics & Phonetics, 37(2), 169-195. DOI: 10.1080/02699206.2022.2039300 Link to postprint manuscript
  • McAllister, T., Eads, A., Kabakoff, H., Scott, M., Boyce, S.E., Whalen, D.H., & Preston, J.L. (2022). Baseline stimulability predicts patterns of response to traditional and ultrasound biofeedback treatment for residual speech sound disorder. Journal of Speech, Language, and Hearing Research, 65(8):2860-2880. DOI: 10.1044/2022_JSLHR-22-00161 Link to postprint and code
  • Kabakoff, H., Gritsyk, O., Harel, D., Tiede, M., Preston, J.L., Whalen, D.H., & McAllister T (2022). Characterizing sensorimotor profiles in children with residual speech sound disorder: a pilot study.  Journal of Communication Disorders,99: 106230 Link to postprint manuscript
  • Peterson, L., Savarese, C., Campbell, T., Ma, Z., Simpson, K. O., & McAllister, T. (2022). Telepractice treatment of residual rhotic errors using app-based biofeedback: A pilot study. Early online, Language, Speech, and Hearing Services in Schools
  • Kabakoff, H., Harel, D., Tiede, M., Whalen, D.H., & McAllister, T. (2021). Extending ultrasound tongue shape complexity measures to speech development and disorders. Journal of Speech, Language, and Hearing Research, 64(7), 2557-2574. 
  • Cheng, H-S., Niziolek, C. A., Buchwald, A., & McAllister, T. (2021). Examining the relationship between speech perception, production distinctness, and production variability.  Frontiers in Human Neuroscience, 15: 660948.
  • Gritsyk, O., Kabakoff, H., Li, J.J., Ayala, S., Shiller, D.M. & McAllister, T. (2021). Toward an index of oral somatosensory acuity: Comparison of three measures in adults. Perspectives of the ASHA Special Interest Groups6(2), 500-512. doi: 10.17605/OSF.IO/2H9JR
  • McAllister, T., Preston, J. L., Hitchcock, E. R., & Hill, J. (2020). Protocol for Correcting Residual Errors with Spectral, ULtrasound, Traditional Speech therapy Randomized Controlled Trial (C-RESULTS RCT). BMC Pediatrics, 20: 66. DOI:
  • Nightingale, C., Swartz, M., Ramig, L. O., & McAllister, T. (2020). Using crowdsourced listeners' ratings to measure speech changes in hypokinetic dysarthria: A proof-of-concept study. American Journal of Speech-Language Pathology. DOI: 10.1044/2019_AJSLP-19-00162
  • Cialdella, L., Kabakoff, H., Preston, J. L., Dugan, S., *Spencer, C., Boyce, S., Tiede, M., Whalen, D.H., & McAllister, T. (2020). Auditory-perceptual acuity in rhotic misarticulation: baseline characteristics and treatment response. Clinical Linguistics & Phonetics. DOI: 10.1080/02699206.2020.1739749
  • Kawitzky, D., & McAllister, T. (2020). The effect of formant biofeedback on the feminization of voice in transgender women. Journal of Voice, 34(1): 53-67.
  • Li, J.J., Ayala, S., Harel, D., Shiller, D, & McAllister, T. (2019). Individual predictors of response to biofeedback training for second-language production. Journal of the Acoustical Society of America, 146(6), 4625. 
  • Preston, J.L., McAllister, T., Phillips, E., Tiede, Boyce, S.E., Tiede, M., Kim, J.S., Whalen, D.H. (2019). Treatment for residual rhotic errors with and without ultrasound visual feedback: A single case experimental study. American Journal of Speech-Language Pathology, 28(3), 1167-1183.  
  • Klaus, A., Lametti, D., Shiller, D, & McAllister, T. (2019.) Can perceptual training alter the effect of visual biofeedback in speech-motor learning? Journal of the Acoustical Society of America, 145(2), 805-817.
  • Harel, D., & McAllister, T. (2019). Multilevel models for communication sciences and disorders. Journal of  Speech, Language, and Hearing Research, 62(4), 783-801.
  • Fernandez, D., Harel, D., Ipeirotis, P., & McAllister, T. (2019). Statistical considerations for crowdsourced perceptual ratings of human speech production. Journal of Applied Statistics, 46(8), 1364-1384.
  • Small, H. C., McAllister, T., & Grigos, M. (2018). Investigating the use of a nonspeech task to measure tongue-jaw differentiation: Findings across typical development. American Journal of Speech-Language Pathology, 27(3), 1030-1038.
  • Preston, J. L., McAllister, T., Phillips, E., Tiede, Boyce, S.E., Tiede, M., Kim, J.S., Whalen, D.H. (2018).  Treatment for residual rhotic errors with high and low frequency ultrasound visual feedback: A single case experimental design. Journal of Speech, Language & Hearing Research, 61(8), 1875-1892.
  • Hamilton Dugan, S., Silbert, N., McAllister Byun, T., Preston, J. L., Sotto, C., & Boyce, S. E. (2019).  Modeling category goodness judgments in children with residual sound errors. Clinical Linguistics & Phonetics, 33(4), 295-315.      
  • McAllister Byun, T. (2017). Efficacy of visual-acoustic biofeedback intervention for residual rhotic errors: A single-subject randomization study. Journal of Speech, Language, and Hearing Research, 60, 1175-1193.
  • McAllister Byun, T., Campbell, H., Liang, W., Park, T.-H., & Svirsky, M. (2017). Enhancing intervention for residual rhotic errors via app-delivered biofeedback: A case study. Journal of Speech, Language, and Hearing Research, 60, 1810-1817.
  • McAllister Byun, T., Hitchcock, E. R., & Ferron, J. M. (2017). Masked visual analysis: Minimizing type I error in response-guided single-case design for communication disorders. Journal of Speech, Language, and Hearing Research, 60(6), 1455-1466.
  • McAllister Byun, T., & Tiede, M. (2017). Perception-production relations in later development of American English rhotics. PLoS ONE 12(2): e0172022. doi:10.1371/journal.pone.0172022
  • Campbell, H., Harel, D., Hitchcock, E., & McAllister Byun, T. (2018). Selecting an acoustic correlate for automated measurement of American English rhotic production in children. International Journal of Speech-Language Pathology, 20(6), 635-643.
  • Campbell, H., & McAllister Byun, T. (2017). Deriving individualized /r/ targets from the acoustics of children’s non-rhotic vowels. Clinical Linguistics and Phonetics, 32(1), 70-87.
  • Hitchcock, E.R., McAllister Byun, T., Swartz, M.T., & Lazarus, R. (2017). Efficacy of electropalatography for treating misarticulation of /r/. American Journal of Speech-Language Pathology, 26(4), 1141-1158.
  • Preston, J.L., McAllister Byun, T., Boyce, S.E., *Hamilton, S., Tiede, M., Phillips, E., Rivera-Campos, A. & Whalen, D.H. (2017). Ultrasound images of the tongue: Applications for assessment and remediation of speech sound errors. Journal of Visualized Experiments, 119, e55123, doi:10.3791/55123.
  • McAllister Byun, T., & Campbell, H. (2017). Differential effects of visual-acoustic biofeedback intervention for residual speech errors. Frontiers in Human Neuroscience, 10. Available at
  • McAllister Byun, T., Inkelas, S., & Rose, Y. (2016). The A-map model: Articulatory reliability in child-specific phonology. Language, 92(1), 141-178.
  • McAllister Byun, T., & Tessier, A.-M. (2016). Motor influences on grammar in an emergentist model of phonology. Language and Linguistics Compass 10(9), pp. 431-452.
  • Long, M.A., Katlowitz, K.A., Svirsky, M., Clary, R.C., McAllister Byun, T., Oki, H., Howard, M.A., Greenlee, J.D.W. (2016). Functional segregation of cortical regions underlying speech timing and articulation. Neuron, 89(6), 1187-1193.
  • McAllister Byun, T., Harel, D., Halpin, P.H., & Szeredi, D. (2016). Deriving gradient measures of child speech from crowdsourced ratings. Journal of Communication Disorders, 64, 91-102.
  • Harel, D., Hitchcock, E. R., Szeredi, D., Ortiz, J., & McAllister Byun, T. (2016). Finding the experts in the crowd: Accuracy and reliability in crowdsourced measures of children's covert contrasts. Clinical Linguistics and Phonetics, 31, 104-117.
  • McAllister Byun, T., & Rose, Y. (2016). Analyzing clinical phonological data using Phon. Seminars in Speech and Language, 37(2), 85-105.
  • McAllister Byun, T., Swartz, M. T., Halpin, P. F., Szeredi, D., & Maas, E. (2016). Direction of attentional focus in biofeedback treatment for /r/ misarticulation. International Journal of Language & Communication Disorders, 51(4), 384-401.
  • McAllister Byun, T., Halpin, P. F., & Szeredi, D. (2015). Online crowdsourcing for efficient rating of speech: A validation study. Journal of Communication Disorders, 53, 70-83.


Critical Evaluation of Research in Communicative Sciences and Disorders

Consideration of the formulation and design of research problems; collection, processing, and interpretation of data. Evaluation of research in speech and speech pathology and audiology.
Course #
CSCD-GE 2109
Communicative Sciences and Disorders

Speech Science: Instrumentation

An advanced and detailed study of the current instrumentation used to evaluate the acoustic, aerodynamic and physiological aspects of speech production in clinical settings and in speech research. Students will gain expertise in the instrumental evaluation of normal subjects.
Course #
CSCD-GE 2125
Communicative Sciences and Disorders