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arXiv · 2601.14850

Multi-Task Transformer for Explainable Speech Deepfake Detection via Formant Modeling

Viola Negroni·Luca Cuccovillo·Paolo Bestagini·Patrick Aichroth·Stefano Tubaro
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Abstract

In this work, we introduce a multi-task transformer for speech deepfake detection, capable of predicting formant trajectories and voicing patterns over time, ultimately classifying speech as real or fake, and highlighting whether its decisions rely more on voiced or unvoiced regions. Building on a prior speaker-formant transformer architecture, we streamline the model with an improved input segmentation strategy, redesign the decoding process, and integrate built-in explainability. Compared to the baseline, our model requires fewer parameters, trains faster, and provides better interpretability, without sacrificing prediction performance.

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Viola Negroni, Luca Cuccovillo, Paolo Bestagini, Patrick Aichroth, Stefano Tubaro. 2026-01-21. Multi-Task Transformer for Explainable Speech Deepfake Detection via Formant Modeling. https://arxiv.org/abs/2601.14850

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