Heterogeneity Over Homogeneity: Investigating Multilingual Speech Pre-trained Models For Detecting Audio Deepfake

Abstract

In this work, we investigate multilingual speech Pre-Trained models (PTMs) for Audio deepfake detection (ADD). We hypothesize that multilingual PTMs trained on large-scale diverse multilingual data gain knowledge about diverse pitches, accents, and tones, during their pre-training phase and making them more robust to variations. As a result, they will be more effective for detecting audio deepfakes. To validate our hypothesis, we extract representations from state-of-the-art (SOTA) PTMs including monolingual, multilingual as well as PTMs trained for speaker and emotion recognition, and evaluated them on ASVSpoof 2019 (ASV), In-the-Wild (ITW), and DECRO benchmark databases. We show that representations from multilingual PTMs, with simple downstream networks, attain the best performance for ADD compared to other PTM representations, which validates our hypothesis. We also explore the possibility of fusion of selected PTM representations for further improvements in ADD, and we propose a f

Stats

• citations11
• S2 citations—
• github stars0
• HF likes0
• heat score8.09
• arxiv keyphukan2024heterogeneity

Related papers

• Investigating Prosodic Signatures Via Speech Pre-trained Models For Audio Deepfake Source Attribution (2024)0.00
• Betray Oneself: A Novel Audio Deepfake Detection Model Via Mono-to-stereo Conversion (2023)10.04
• MLAAD: The Multi-language Audio Anti-spoofing Dataset (2024)13.34
• SLIM: Style-linguistics Mismatch Model For Generalized Audio Deepfake Detection (2024)4.52
• AUDETER: A Large-scale Dataset For Deepfake Audio Detection In Open Worlds (2025)0.00
• Hm-conformer: A Conformer-based Audio Deepfake Detection System With Hierarchical Pooling And Multi-level Classification Token Aggregation Methods (2023)9.03
• Transsionadd: A Multi-frame Reinforcement Based Sequence Tagging Model For Audio Deepfake Detection (2023)0.00
• Pitch Imperfect: Detecting Audio Deepfakes Through Acoustic Prosodic Analysis (2025)0.00