6 papers
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…
WhispSynth: Scaling Multilingual Whisper Corpus through Real Data Curation and A Novel Pitch-free Generative Framework
Tianyi Tan, Jiaxin Ye, Yuanming Zhang +4
Whisper generation is constrained by the difficulty of data collection. Because whispered speech has low acoustic amplitude, high-fidelity recording is challenging. In this paper,…
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…
RaD-Net 2: A causal two-stage repairing and denoising speech enhancement network with knowledge distillation and complex axial self-attention
Mingshuai Liu, Zhuangqi Chen, Xiaopeng Yan +5
In real-time speech communication systems, speech signals are often degraded by multiple distortions. Recently, a two-stage Repair-and-Denoising network (RaD-Net) was proposed with…
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…