Konstantinos Papadopoulos and Eleni Koustriava
2015
Accessibility, Greek, Discernment
The present study examines the comprehension of texts presented via synthetic and natural speech in individuals with and without visual impairments. Twenty adults with visual impairments and 65 sighted adults participated in the study.
Deepfake Defense: Constructing and Evaluating a Specialized Urdu Deepfake Audio Dataset
Sheza Munir, Wassay Sajjad, Mukeet Raza, Emaan Mujahid Abbas, Abdul Hameed Azeemi, Ihsan Ayyub Qazi, Agha Ali Raza
2023
Discernment, Detection, Dataset, Urdu
This paper addresses the escalating challenges posed by deepfake attacks on Automatic Speaker Verification (ASV) systems. We present a novel Urdu deepfake audio dataset for deepfake detection, focusing on two spoofing attacks – Tacotron and VITS TTS.
Evaluating Comprehension of Natural and Synthetic Conversational Speech
Mirjam Wester, Oliver Watts and Gustav Eje Henter
2016
AI x Human Dialogue, Discernment, English
In an effort to develop more ecologically relevant evaluation techniques that go beyond isolated sentences, this paper investigates comprehension of natural and synthetic speech dialogues.
Generation and Detection of Sign Language Deepfakes – A Linguistic and Visual Analysis
Shahzeb Nacem, Muhammad Riyyan Khan, Usman Tariq, Abhinav Dhall, Carlos Ivan Colon, Hasan Al-Nashash
2024
Generation, Discernment, Detection, Dataset, Accessibility, American Sign Language
This research presents a positive application of deepfake technology in upper body generation, while performing sign-language for the Deaf and Hard of Hearing (DHoH) community.
Chaeeun Han, Prasenjit Mitra, Syed Masum Billah
2024
Discernment, Accessibility, English
This paper explores how blind and sighted individuals perceive real and spoofed audio, highlighting differences and similarities between the groups.