mlsanityData to 7 Oct 2026

How to Label Resynthesized Audio: The Dual Role of Neural Audio Codecs in Audio Deepfake Detection

arXiv 2602.16343 ↗First posted 18 Feb 2026cs.SD cs.LGcited by 0

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Abstract (arXiv)

Since Text-to-Speech systems typically don't produce waveforms directly, recent spoof detection studies use resynthesized waveforms from vocoders and neural audio codecs to simulate an attacker. Unlike vocoders, which are specifically designed for speech synthesis, neural audio codecs were originally developed for compressing audio for storage and transmission. However, their ability to discretize speech also sparked interest in language-modeling-based speech synthesis. Owing to this dual functionality, codec resynthesized data may be labeled as either bonafide or spoof. So far, very little research has addressed this issue. In this study, we present a challenging extension of the ASVspoof 5 dataset constructed for this purpose. We examine how different labeling choices affect detection performance and provide insights into labeling strategies.

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References · 20

  1. 2024The Llama 3 Herd of Modelscited by 14,192
  2. 2023Neural Codec Language Models are Zero-Shot Text to Speech Synthesizerscited by 737
  3. 2022High Fidelity Neural Audio Compressioncited by 673
  4. 2024Moshi: a speech-text foundation model for real-time dialoguecited by 536
  5. 2023High-Fidelity Audio Compression with Improved RVQGANcited by 423
  6. 2024CosyVoice: A Scalable Multilingual Zero-shot Text-to-speech Synthesizer based on Supervised Semantic Tokenscited by 323
  7. 2024CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Modelscited by 282
  8. 2021AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networkscited by 173
  9. 2025Qwen2.5-1M Technical Reportcited by 158
  10. 2025CosyVoice 3: Towards In-the-wild Speech Generation via Scaling-up and Post-trainingcited by 142
  11. 2022Does Audio Deepfake Detection Generalize?cited by 129
  12. 2024FunAudioLLM: Voice Understanding and Generation Foundation Models for Natural Interaction Between Humans and LLMscited by 118
8 more
  1. 2024ASVspoof 5: Crowdsourced Speech Data, Deepfakes, and Adversarial Attacks at Scalecited by 88
  2. 2025Llasa: Scaling Train-Time and Inference-Time Compute for Llama-based Speech Synthesiscited by 69
  3. 2021RawBoost: A Raw Data Boosting and Augmentation Method applied to Automatic Speaker Verification Anti-Spoofingcited by 64
  4. 2025ASVspoof 5: Design, Collection and Validation of Resources for Spoofing, Deepfake, and Adversarial Attack Detection Using Crowdsourced Speechcited by 25
  5. 2024CodecFake: Enhancing Anti-Spoofing Models Against Deepfake Audios from Codec-Based Speech Synthesis Systemscited by 15
  6. 2016High-Quality, Low-Delay Music Coding in the Opus Codeccited by 12
  7. 2025CodecFake+: Codec-Based Resynthesized Data as a Proxy for Detecting CodecFake Speechcited by 6
  8. 2025MARS6: A Small and Robust Hierarchical-Codec Text-to-Speech Modelcited by 1

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