Detecting the Undetectable: Assessing the Efficacy of Current Spoof
Detection Methods Against Seamless Speech Edits
Detecting the Undetectable: Assessing the Efficacy of Current Spoof
Detection Methods Against Seamless Speech Edits
Neural speech editing advancements have raised concerns about their misuse in spoofing attacks. Traditional partially edited speech corpora primarily focus on cut-and-paste edits, which, while maintaining speaker consistency, often introduce detectable discontinuities. Recent methods, like A\textsuperscript{3}T and Voicebox, improve transitions by leveraging contextual information. To foster spoofing detection research, we …