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Meisam Khalil Arjmandi, Ph.D.

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Biography
Michigan State UniversityPh.D.Communication Sciences and Disorders
Michigan State UniversitySpecializationCognitive Science
Shahed UniversityM.Sc.Biomedical Engineering
2018 - 2019
Doctoral Dissertation Fellowship Award
2018 - 2019
The Charles J. Strosacker Foundation Award
2017 - 2019
Acoustical Society of America Student Travel Award

Bibliographic
Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
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PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. (Note that publications are often cited in additional ways that are not shown here.) Fields are based on how the National Library of Medicine (NLM) classifies the publication's journal and might not represent the specific topic of the publication. Translation tags are based on the publication type and the MeSH terms NLM assigns to the publication. Some publications (especially newer ones and publications not in PubMed) might not yet be assigned Field or Translation tags.) Click a Field or Translation tag to filter the publications.
  1. Lehet M, Arjmandi MK, Houston D, Dilley L. Circumspection in using automated measures: Talker gender and addressee affect error rates for adult speech detection in the Language ENvironment Analysis (LENA) system. Behav Res Methods. 2021 02; 53(1):113-138. PMID: 32583366.
    Citations: 1     Fields:    Translation:Humans
  2. Arjmandi M, Houston D, Wang Y, Dilley L. Estimating the reduced benefit of infant-directed speech in cochlear implant-related speech processing. Neurosci Res. 2021 Oct; 171:49-61. PMID: 33484749.
    Citations:    Fields:    Translation:Humans
  3. Dilley L, Lehet M, Wieland EA, Arjmandi MK, Kondaurova M, Wang Y, Reed J, Svirsky M, Houston D, Bergeson T. Individual Differences in Mothers' Spontaneous Infant-Directed Speech Predict Language Attainment in Children With Cochlear Implants. J Speech Lang Hear Res. 2020 07 20; 63(7):2453-2467. PMID: 32603621.
    Citations: 1     Fields:    Translation:Humans
  4. Woodard, J. C., Losievski, N., Arjmandi, M. K., Lehet, M., Wang, Y., Houston, D., & Dilley, L. Accuracy of the language environment analysis (LENA) speech processing system for detecting communicative vocalizations of young children. The Journal of the Acoustical Society of America. 2019; 146(4):2956-2956. View Publication.
  5. Banks, R., Arjmandi, M. K., Ghasemzadeh, H., & Berardi, M. Formant Dynamics in Vowel Pronunciation as Acoustic Correlates of Concussed Speech. 13th World Congress on Brain Injury. 2019; 33:2-3. View Publication.
  6. Banks, R., Arjmandi, M. K., Ghasemzadeh, H., & Berardi, M. Application of Automated Vowel Space Area Analysis to Predict Concussion Status. 13th World Congress on Brain Injury. 2019; 33:1-2. View Publication.
  7. Arjmandi, M. K., Ghasemzadeh, H., & Dilley, L. Simulated cochlear-implant processing results in major loss of acoustic information regarding differences in talkers’ voice qualities. The Journal of the Acoustical Society of America. 2019; 145(1690). View Publication.
  8. Kathiresan, T., Dilley, L., Townsend, S., Shi, R., Daum, M., Arjmandi, M. K., & Dellwo, V. Infant-directed speech enhances recognizability of individual mothers’ voices. The Journal of the Acoustical Society of America. 2019; 145(1766). View Publication.
  9. Arjmandi, M. K., Dilley, L., Wang, Y., Svirsky, M., Lehet, M., & Houston, D. Separability of infant-directed from adult-directed speech is affected by number of channels in cochlear-implant simulated speech. The Journal of the Acoustical Society of America. 2019; 3(145):1766-1766. View Publication.
  10. Arjmandi, M.K. Early Linguistic Environments and Language Development in Children with Cochlear Implants. 2019. View Publication.
  11. Ghasemzadeh, H., & Arjmandi, M. K. Toward Optimum Quantification of Pathology-induced Noises: An Investigation of Information Missed by Human Auditory System. IEEE/ACM Transactions on Audio, Speech, and Language Processing. 2019; 28: 519 - 528. View Publication.
  12. Arjmandi, M. K., Houston, D., Svirsky, M., Wang, Y., Lehet, M., & Dilley, L. Individual differences across caregivers in acoustic implementation of infant-directed and adult-directed speech: Modeling impacts on intelligibility in children with cochlear implants. The Journal of the Acoustical Society of America. 2019; 4(146):2921-2921. View Publication.
  13. Ghasemzadeh, H., & Arjmandi, M. K. Optimum solution and evaluation of rectangular jigsaw puzzles based on branch and bound method and combinatorial accuracy. Multimedia Tools and Applications. 2018; 6(77):6837-6861. View Publication.
  14. Arjmandi, M. K., Dilley, L. C., & Wagner, S. E. Investigation of acoustic dimension use in dialect production: machine learning of sonorant sounds for modeling acoustic cues of African American dialect. 11th International Conference on Voice Physiology and Biomechanics (ICVPB 2018). 2018. View Publication.
  15. Arjmandi, M. K., Dilley, L. C., & Lehet, M. A comprehensive framework for F0 estimation and sampling in modeling prosodic variation in infantdirected speech. Sixth International Symposium on Tonal Aspects of Languages. 2018; 72-76. View Publication.
  16. Arjmandi, M. K., Dilley, L., & Wagner, S. Acoustic cues to linguistic profiling? Machine learning of phonetic features of African American English. The Journal of the Acoustical Society of America. 2018; 3(143):1969-1969. View Publication.
  17. Dilley, L., Wieland, E., Lehet, M., Arjmandi, M. K., Houston, D., & Bergeson, T. Quality and quantity of infant-directed speech by maternal caregivers predicts later speech-language outcomes in children with cochlear implants. The Journal of the Acoustical Society of America. 2018; 3(143):1822-1822. View Publication.
  18. Lehet, M., Arjmandi, M. K., Dilley, L. C., Roy, S., & Houston, D. Fidelity of automatic speech processing for adult speech classifications using the Language ENvironment Analysis (LENA) system. Proceedings of Interspeech. 2018; 3-7. View Publication.
  19. Ghasemzadeh, H., & Arjmandi, M. K. Universal audio steganalysis based on calibration and reversed frequency resolution of human auditory system. IET Signal Processing. 2017; 8(11):916-922. View Publication.
  20. Dilley, L., Arjmandi, M. K., & Ireland, Z. Spectro-temporal cues for perceptual recovery of reduced syllables from continuous, casual speech. The Journal of the Acoustical Society of America. 2017; 5(141):3700-3700. View Publication.
  21. Ghasemzadeh, H., Khass, M. T., & Arjmandi, M. K. Audio steganalysis based on reversed psychoacoustic model of human hearing. Digital signal processing. 2016; 51:133-141. View Publication.
  22. Akbari, A., & Arjmandi, M. K. Employing linear prediction residual signal of wavelet sub-bands in automatic detection of laryngeal pathology. Biomedical signal processing and control. 2015; 18:293-302. View Publication.
  23. Ghasemzadeh, H., Khass, M. T., Arjmandi, M. K., & Pooyan, M. Detection of vocal disorders based on phase space parameters and Lyapunov spectrum. Biomedical signal processing and control. 2015; 22:135-145. View Publication.
  24. Akbari, A., & Arjmandi, M. K. An efficient voice pathology classification scheme based on applying multi-layer linear discriminant analysis to wavelet packet-based features. Biomedical signal processing. 2014; 10:209-223. View Publication.
  25. Arjmandi, M. K., & Pooyan, M. An optimum algorithm in pathological voice quality assessment using wavelet-packet-based features, linear discriminant analysis and support vector machine. Biomedical signal processing. 2012; 7(1):3-19. View Publication.
  26. Arjmandi MK, Pooyan M, Mikaili M, Vali M, Moqarehzadeh A. Identification of voice disorders using long-time features and support vector machine with different feature reduction methods. J Voice. 2011 Nov; 25(6):e275-89. PMID: 21186096.
    Citations: 6     Fields:    Translation:Humans
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Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.