How Deep Are the Fakes? Focusing on Audio Deepfake: A Survey. - Zahra Khanjani; Gabrielle Watson; Vandana P. Janeja (CoRR, 2021)

Audio Deepfake Perceptions in College Going Populations. - Gabrielle Watson; Zahra Khanjani; Vandana P. Janeja (CoRR, 2021)

Audio deepfakes: A survey. - Zahra Khanjani; Gabrielle Watson; Vandana P. Janeja (Frontiers Big Data, 2022)

Learning to Listen and Listening to Learn: Spoofed Audio Detection Through Linguistic Data Augmentation. - Zahra Khanjani; Lavon Davis; Anna Tuz; Kifekachukwu Nwosu; Christine Mallinson; Vandana P. Janeja (ISI, 2023)

Investigating Causal Cues: Strengthening Spoofed Audio Detection with Human-Discernible Linguistic Features. - Zahra Khanjani; Tolulope Ale; Jianwu Wang 001; Lavon Davis; Christine Mallinson; Vandana P. Janeja (CoRR, 2024)

ALDAS: Audio-Linguistic Data Augmentation for Spoofed Audio Detection. - Zahra Khanjani; Christine Mallinson; James R. Foulds; Vandana P. Janeja (CoRR, 2024)

A place for (socio)linguistics in audio deepfake detection and discernment: Opportunities for convergence and interdisciplinary collaboration. - Christine Mallinson; Vandana P. Janeja; Chloe Evered; Zahra Khanjani; Lavon Davis; Noshaba Nasir Bhalli; Kifekachukwu Nwosu (Lang. Linguistics Compass, 2024)

Blue Sky: Expert-in-the-Loop Representation Learning Framework for Audio Anti-Spoofing: Multimodal, Multilingual, Multi-speaker, Multi-attack (4M) Scenarios. - Zahra Khanjani; Vandana P. Janeja; Christine Mallinson; Sanjay Purushotham (SDM, 2025)