#AudioDeepFake
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🎙️ Are synthetic speech artifacts evenly distributed across phonemes? Not quite!

In our latest paper in MTAP, we propose a phonetic-driven framework using PPGs & phoneme pruning, boosting anti-spoofing performance on ASVspoof 2019 LA.

🔗 link.springer.com/article/10.1...

#SpeechAI #AudioDeepfake
Client Challenge
link.springer.com
September 18, 2026 at 6:21 AM
🎙️ Does knowing a speaker’s gender actually boost speaker recognition?

In our latest paper in Soft Computing (Springer), we explore gender effects via bio-inspired filterbanks (Gammatone, Cascade, etc.)

🔗 link.springer.com/article/10.1...

#SpeechProcessing #AudioAI #AudioDeepFake #ISPlab
Exploring gender effects in speaker recognition systems through frequency domain analysis by convolutional neural networks - Soft Computing
Advances in deep learning have led to significant progress in the field of speech processing, particularly in applications such as speaker recognition systems (SRSs). Additional information such as ge...
link.springer.com
September 20, 2026 at 3:58 AM
In our new paper in IEEE Access, we use Log-Area Ratios (LARs) + a novel Conditional Speaker Normalization (CSN) conditioned on speaker proxies (e.g. height) to detect synthetic speech reliably on ASVspoof & FoR.

ieeexplore.ieee.org/abstract/doc...

#DeepfakeDetection #SpeechAI #AudioDeepfake
Conditional Speaker Normalization of Vocal Tract Shape Features for Robust Synthetic Speech Detection
The rapid advancement of text-to-speech and voice conversion technologies has significantly improved the quality of synthetic speech, posing increasing challenges for developing reliable detection cou...
ieeexplore.ieee.org
September 20, 2026 at 4:04 AM
A forensic similarity method can tell if two speech clips share the same manipulation traces, using a shallow similarity network—without large labelled data (Oct 3 2025). Read more: https://getnews.me/forensic-similarity-technique-advances-speech-deepfake-detection/ #audiodeepfake #forensics
October 6, 2025 at 8:28 AM
AUDDT, an open‑source toolkit, combines 28 public audio deepfake datasets for benchmarking pretrained detectors; initial tests show accuracy drops on out‑of‑domain data. Read more: https://getnews.me/auddt-open-source-toolkit-for-benchmarking-audio-deepfake-detection/ #auddt #audiodeepfake
September 29, 2025 at 5:36 PM
A new framework detects zero‑day audio deepfakes with retrieval‑based voice profiling, achieving performance on par with fine‑tuned models on DeepFake‑Eval‑2024. Read more: https://getnews.me/zero-day-audio-deepfake-detection-with-retrieval-and-profile-matching/ #audiodeepfake #zeroday
September 29, 2025 at 8:07 AM
The new LAVA framework for voice attribution reports ADA F1 scores above 95% and ADMR macro F1 of 96.31% across six model classes, with confidence‑based rejection for unknown attacks. https://getnews.me/lava-framework-boosts-audio-deepfake-attribution-and-model-recognition/ #lavaa #audiodeepfake
September 17, 2025 at 12:36 PM
Audio-Deepfakes – zunehmende KI-Verfügbarkeit lässt Betrugsversuche rasant ansteigen

#AudioDeepfake #Betrug #Deepfake #HumanRiskManagement #KITool @KnowBe4 #SecurityAwareness #Sicherheitsbewusstsein #Sprachanrufe

netzpalaver.de/2025/...
July 2, 2025 at 11:36 AM