5 papers · 1 filter
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…
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…
UniFlow: Unifying Speech Front-End Tasks via Continuous Generative Modeling
Ziqian Wang, Zikai Liu, Yike Zhu +6
Generative modeling has recently achieved remarkable success across image, video, and audio domains, demonstrating powerful capabilities for unified representation learning. Yet sp…
BS-PLCNet 2: Two-stage Band-split Packet Loss Concealment Network with Intra-model Knowledge Distillation
Zihan Zhang, Xianjun Xia, Chuanzeng Huang +2
Audio packet loss is an inevitable problem in real-time speech communication. A band-split packet loss concealment network (BS-PLCNet) targeting full-band signals was recently prop…
BS-PLCNet: Band-split Packet Loss Concealment Network with Multi-task Learning Framework and Multi-discriminators
Zihan Zhang, Jiayao Sun, Xianjun Xia +3
Packet loss is a common and unavoidable problem in voice over internet phone (VoIP) systems. To deal with the problem, we propose a band-split packet loss concealment network (BS-P…