Publications

 

Journal Papers

  1. Mallinson, C., Janeja, V. P., Evered, C., Khanjani, Z., Davis, L., Bhalli, N. N., & Nwosu, K. (2024). A place for (socio) linguistics in audio deepfake detection and discernment: Opportunities for convergence and interdisciplinary collaboration. Language and Linguistics Compass, 18(5), https://doi.org/10.1111/lnc3.12527
  2. Evered, Chloe. 2024. “A place for linguistics in combating disinformation by audio deepfakes.” UMBC Review, 25. 151-164. https://ur.umbc.edu/wp-content/uploads/sites/354/2024/04/UMBC_Review_2024Volume-25_Digital.pdf
  3. Khanjani, Z., Watson, G., & Janeja, V. P. (2023). Audio deepfakes: A survey. Frontiers in Big Data, 5, 1001063

Conference Paper

  1. Khanjani, Z., Davis, L., Tuz, A., Nwosu, K., Mallinson, C., & Janeja, V. P. (2023, October). Learning to listen and listening to learn: Spoofed audio detection through linguistic data augmentation. In 2023 IEEE International Conference on Intelligence and Security Informatics (ISI) (pp. 01-06). IEEE.

Conference Presentation

  1. Evered, C., Mallinson, C., Davis, L., Janeja, V. P., Bhalli, N. B., Khanjani, Z., Naqvi, N., & Nwosu, K. (2024). Sociolinguistically-informed educational trainings for audio deepfake discernment [Conference presentation]. British Association for Applied Linguistics 2024 conference (BAAL 2024). University of Essex, UK.

Pre-Print

  1. Vandana P. Janeja, Christine Mallinson, Toward Transdisciplinary Approaches to Audio Deepfake Discernment, arXiv:2411.05969, 2024
  2. Khanjani, Z., Ale, T., Wang, J., Davis, L., Mallinson, C., & Janeja, V. P. (2024). Investigating Causal Cues: Strengthening Spoofed Audio Detection with Human-Discernible Linguistic Features. arXiv preprint arXiv:2409.06033.
  3. Khanjani, Z., Mallinson, C., Foulds, J & Janeja, V. P. (2024). ALDAS: Audio-Linguistic Data Augmentation for Spoofed Audio Detection. arXiv preprint arXiv:2410.15577
  4. Noshaba N. Bhalli, Nehal Naqvi, Chloe Evered, Christine Mallinson, Vandana P. Janeja, Listening for Expert Identified Linguistic Features: Assessment of Audio Deepfake Discernment among Undergraduate Students. arXiv preprint arXiv.2411.14586
  5. Watson, G., Khanjani, Z., & Janeja, V. P. (2021). Audio deepfake perceptions in college going populations. arXiv preprint arXiv:2112.03351.
  6. Watson, G., Khanjani, Z., & Janeja, V. P. (2021). How Deep Are the Fakes? Focusing on Audio Deepfake: A Survey. arXiv preprint arXiv:2111.14203.

Conference Poster

  1. Nwosu, K., Evered, C., Khanjani, Z., Bhalli, N., Davis, L., Mallinson, C., & Janeja, V. P. (2023). Auto Annotation of Linguistic Features for Audio Deepfake Discernment. In Proceedings of the AAAI Symposium Series (Vol. 2, No. 1, pp. 242-244).
  2. Davis, L., Khanjani, Z., Bhali, N., Janeja, V., Mallinson, C. (2023) Training Students to Listen Better: Advancing Deepfake Audio Discernment. 7th Annual UMBC Provost’s Teaching and Learning Symposium. Baltimore, MD.
  3. Davis, L., Khanjani, Z., Bhali, N., Janeja, V., Mallinson, C. (2023) Training Students to Listen Better: Advancing Deepfake Audio Discernment. 7th Annual UMBC Provost’s Teaching and Learning Symposium. Baltimore, MD.

Op Ed

  1. Mallinson, Christine, and Vandana Janeja. (2024, March). “Commentary: Bringing people and technology together to combat the threat of deepfakes.” Maryland Matters. https://www.marylandmatters.org/2024/03/25/commentary-bringing-people-and-technology-together-to-combat-the-threat-of-deepfakes/

Gallery Exhibit

  1. Mallinson, C., Janeja, V. P., Evered, C., Nwosu, K., Davis, L., Khanjani, Z., & Bhalli, N. B. (2024). “Can You Catch a Deepfake?” Gallery exhibit and accompanying research presentation as part of the Spring 2024 faculty research show. UMBC Center for Art, Design, and Visual Culture. January-March.

Talks

  1. V.P. Janeja, Transdisciplinarity in Audio Deepfake Discernment with Expert-in-the-loop AI Models , Talk at the Federal Information Integrity R&D Interagency Working Group (IIRD IWG), March 22, 2024
  2. V.P. Janeja, Transdisciplinarity in Audio Deepfake Discernment with Expert-in-the-loop AI Models , Talk at the Cyber Defense Lab at UMBC October, 2024
  3. Khanjani, Z., Evered, C., Mallinson, C., Janeja, P. (2024) Strengthening AI Models for Spoofed Audio Detection: An Interdisciplinary Approach Incorporating Linguistic Knowledge, Academic Data Sicence Alliance (ADSA) Annual Meeting
  4. Mallinson, Christine. 2024. “What Does Language Do and What Can We Do With It?” University lecture delivered as the 2023-24 Lipitz Distinguished Professor of Arts, Humanities and Social Sciences at UMBC. April.