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Robust Audio-Visual Target Speaker Extraction with Emotion-Aware Multiple Enrollment Fusion
Zhan Jin, Bang Zeng, Peijun Yang +5
Audio-Visual Target Speaker Extraction (AVTSE) is crucial for cocktail party scenarios. Leveraging multiple cues --such as utterance-level speaker embeddings or steady face images,…
SEF-MK: Speaker-Embedding-Free Voice Anonymization through Multi-k-means Quantization
Beilong Tang, Xiaoxiao Miao, Xin Wang +1
Voice anonymization protects speaker privacy by concealing identity while preserving linguistic and paralinguistic content. Self-supervised learning (SSL) representations encode li…
LauraTSE: Target Speaker Extraction using Auto-Regressive Decoder-Only Language Models
Beilong Tang, Bang Zeng, Ming Li
We propose LauraTSE, an Auto-Regressive Decoder-Only Language Model for Target Speaker Extraction built upon the LauraGPT backbone. LauraTSE employs a small-scale auto-regressive d…
Universal Speaker Embedding Free Target Speaker Extraction and Personal Voice Activity Detection
Bang Zeng, Ming Li
Determining 'who spoke what and when' remains challenging in real-world applications. In typical scenarios, Speaker Diarization (SD) is employed to address the problem of 'who spok…