Phoneme Discretized Saliency Maps for Explainable Detection of AI-Generated Voice
<|reference_start|>Phoneme Discretized Saliency Maps for Explainable Detection of AI-Generated Voice: In this paper, we propose Phoneme Discretized Saliency Maps (PDSM), a discretization algorithm for saliency maps that takes advantage of phoneme boundaries for explainable detection of AI-generated voice. We experimentally show with two different Text-to-Speech systems (i.e., Tacotron2 and Fastspeech2) that the proposed algorithm produces saliency maps that result in more faithful explanations compared to standard posthoc explanation methods. Moreover, by associating the saliency maps to the phoneme representations, this methodology generates explanations that tend to be more understandable than standard saliency maps on magnitude spectrograms.<|reference_end|>
@article{gupta2024phoneme,
    title={Phoneme Discretized Saliency Maps for Explainable Detection of
  AI-Generated Voice},
    author={Shubham Gupta and Mirco Ravanelli and Pascal Germain and Cem Subakan},
    journal={arXiv preprint arXiv:2406.10422},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.10422},
    primaryClass={eess.AS cs.SD eess.SP}
}