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eess.AS2026
G-MaP-SE: Guided Speech Enhancement via GMM-Based Prior Matching
Yike Zhu, Ziqian Wang, Zikai Liu +5
Using speaker embeddings as conditioning can strengthen speech enhancement, but most methods either require clean enrollment audio or rely on embeddings extracted from noisy speech…
eess.AS2026
EvoTSE: Evolving Enrollment for Target Speaker Extraction
Zikai Liu, Ziqian Wang, Xingchen Li +4
Target Speaker Extraction (TSE) aims to isolate a specific speaker's voice from a mixture, guided by a pre-recorded enrollment. While TSE bypasses the global permutation ambiguity…
eess.AS2026
SVoice: Style-Aware Autoregressive Modeling with Enhanced Conditioning for Singing Style Conversion
Ziqian Wang, Xianjun Xia, Chuanzeng Huang +1
We present SVoice, the winning system of the Singing Voice Conversion Challenge (SVCC) 2025 for both the in-domain and zero-shot singing style conversion tracks. Built on the s…