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Universal Speech Content Factorization
Henry Li Xinyuan, Zexin Cai, Lin Zhang +5
We propose Universal Speech Content Factorization (USCF), a simple and invertible linear method for extracting a low-rank speech representation in which speaker timbre is suppresse…
Dimensionality-Aware Anomaly Detection in Learned Representations of Self-Supervised Speech Models
Sandra Arcos-Holzinger, Sarah M. Erfani, James Bailey +1
Self-supervised speech models (S3Ms) achieve strong downstream performance, yet their learned representations remain poorly understood under natural and adversarial perturbations.…
Integrated Spoofing-Robust Automatic Speaker Verification via a Three-Class Formulation and LLR
Kai Tan, Lin Zhang, Ruiteng Zhang +6
Spoofing-robust automatic speaker verification (SASV) aims to integrate automatic speaker verification (ASV) and countermeasure (CM). A popular solution is fusion of independent AS…
Can LLMs Help Localize Fake Words in Partially Fake Speech?
Lin Zhang, Thomas Thebaud, Zexin Cai +5
Large language models (LLMs), trained on large-scale text, have recently attracted significant attention for their strong performance across many tasks. Motivated by this, we inves…
SE-DiCoW: Self-Enrolled Diarization-Conditioned Whisper
Alexander Polok, Dominik Klement, Samuele Cornell +4
Speaker-attributed automatic speech recognition (ASR) in multi-speaker environments remains a major challenge. While some approaches achieve strong performance when fine-tuned on s…
SpatialEmb: Extract and Encode Spatial Information for 1-Stage Multi-channel Multi-speaker ASR on Arbitrary Microphone Arrays
Yiwen Shao, Yong Xu, Sanjeev Khudanpur +1
Spatial information is a critical clue for multi-channel multi-speaker target speech recognition. Most state-of-the-art multi-channel Automatic Speech Recognition (ASR) systems ext…