activity
20242026
collaborators
Showing cs.SDShow all

9 papers · 1 filter

cs.SD2026

FlowGRPO for Vocal Separation: From Reward Analysis to Reward Design

Lishi Zuo, Chong-Xin Gan, Zezhong Jin +3

The Flow Matching objective supervises the velocity field at intermediate states, whereas waveform metrics are evaluated after decoding and may be non-differentiable. To align Flow…

cs.SD2026

TS-SP: Learning Speaker-Preserving Representations in Audio Large Language Models

Junjie Li, Zheng Liang, Zhe Li +2

Audio large language models (ALLMs) can understand speech content, yet their ability to use speaker identity for verification remains limited. We propose TS-SP (Two-Stage Speaker P…

cs.SD2026

A Unified Uncertainty-Aware Back-End for Speaker Verification: Scoring, Normalization, and Calibration

Junjie Li, Kong Aik Lee

Speaker verification back-ends commonly combine similarity scoring, score normalization, and calibration. However, speaker embeddings extracted from real-world utterances have tria…

cs.SD2026

Decoupled Latent Flow Matching for Few-Step Joint Vocal-Accompaniment Separation

Lishi Zuo, Youzhi Tu, Lu Yi +4

Generative modeling provides a flexible way to model mixture-conditioned source distributions, but iterative diffusion and flow matching models are costly for long music signals. T…

cs.SD2026

Beyond Residual Connections: Manifold-Constrained Hyper-Connections for Robust Speaker Representation Learning

Zezhong Jin, Xiaoyu Wang, Zhe Li +4

Residual connections are fundamental to deep speaker recogni- tion models, such as ECAPA-TDNN and ResNet. However, standard identity mapping limits information flow to a sin- gle p…

cs.SD2026

Towards Robust Uncertainty-Aware Speaker Modeling

Junjie Li, Yang Xiao, Kong Aik Lee

Speaker embeddings aggregate frame-level acoustic features into compact representations for speaker recognition. Recent uncertainty-aware speaker modeling approaches further charac…

cs.SD2025

Xi+: Uncertainty Supervision for Robust Speaker Embedding

Junjie Li, Kong Aik Lee, Duc-Tuan Truong +2

There are various factors that can influence the performance of speaker recognition systems, such as emotion, language and other speaker-related or context-related variations. Sinc…

cs.SD2024

On the effectiveness of enrollment speech augmentation for Target Speaker Extraction

Junjie Li, Ke Zhang, Shuai Wang +3

Deep learning technologies have significantly advanced the performance of target speaker extraction (TSE) tasks. To enhance the generalization and robustness of these algorithms wh…

cs.SD2024

VoxGenesis: Unsupervised Discovery of Latent Speaker Manifold for Speech Synthesis

Weiwei Lin, Chenhang He, Man-Wai Mak +2

Achieving nuanced and accurate emulation of human voice has been a longstanding goal in artificial intelligence. Although significant progress has been made in recent years, the ma…