(*student co-author)
Li, J., *Fan, X., Lavechin, M., Cristia, A., Garcia, P., McElwain, N. L., & Hasegawa-Johnson, M. (2025). Automated analysis of naturalistic recordings in early childhood: Applications, challenges, and opportunities. IEEE Signal Processing Magazine, 42 (6), 16-34. doi: 10.1109/MSP.2025.3610974
Fan, X., Li, J., McElwain, N. L., & Hasegawa-Johnson (accepted). Band-split self-supervised Mamba for infant-centered audio analysis. Proc. INTERSPEECH 2025.
*Khan, M.N., McElwain, N. L., Hasegawa-Johnson, M., & Islam, B. (accepted). InfantMotion2Vec: Unlabeled data-driven infant pose estimation using a single chest IMU; IEEE International Conference on Wearable and Implantable Body Sensor Networks (BSN 2024).
*Khan, M.N., *Li, J., McElwain, N. L., Hasegawa-Johnson, M., & Islam, B. (2024). Sound tagging in infant-centric home soundscapes. Proceedings of 9th IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE 2024). https://arxiv.org/abs/2406.17190
*Li, J., Hasegawa-Johnson, M., & McElwain, N. L. (2024). Analysis of self-supervised speech models on children’s speech and infant vocalizations. IEEE ICASSP Workshop of Self-supervision in Audio, Speech and Beyond (SASB). https://ieeexplore.ieee.org/document/10626416
Islam, B., McElwain, N L., *Li, J., Davila, M., *Hu, Y., *Hu, K., Bodway, J., Dhekne, A., Roy Choudhury, R., & Hasegawa-Johnson, M. (2024). A preliminary technical validation of LittleBeats™: A multimodal sensing platform for assessing cardiac physiology, motion, and vocalizations. Sensors, 24(3), 901. https://doi.org/10.3390/s24030901
McElwain, N. L., Fisher, M., Nebeker, C., Bodway, J. M., Islam, B., & Hasegawa-Johnson, M. (2024). Evaluating users’ experiences of a child multimodal wearable device: Mixed Methods Approach. JMIR Human Factors. Feb 8;11:e49316. doi: 10.2196/49316.
*Chang, J., Hasegawa-Johnson, M., McElwain, N. L., & Islam, B. (2023). Classification of infant sleep/wake states: Cross-attention among large scale pretrained transformer networks using audio, ECG, and IMU data. Proc. 2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Taipei, Taiwan, pp. 2370-2377, doi: 10.1109/APSIPAASC58517.2023.10317201.
*Li, J., Hasegawa-Johnson, M., & McElwain, N. L. (2023). Towards robust family-infant audio analysis based on unsupervised pretraining of Wav2Vec 2.0 on large-scale unlabeled family audio. INTERSPEECH 2023. Preprint available here: https://arxiv.org/abs/2305.12530v2