7 papers · 1 filter
PACodec: A Low-bitrate Neural Speech Codec with Parallel Additive Vector Quantization
Fei Liu, Yang Ai, Xiao-Hang Jiang +1
This paper proposes PACodec, a novel low-bitrate neural speech codec based on parallel additive vector quantization (PAVQ). Unlike the mainstream residual vector quantization (RVQ)…
Neural Music Enhancement with Dual Time-Frequency Spectral Representations for Prediction and Discrimination
Fei Liu, Yang Ai, Zhen-Hua Ling
Non-professional music recordings shared online often suffer from background noise and reverberation, degrading perceived quality and limiting reuse. This paper proposes DSME, a mu…
LatentFlowSR: High-Fidelity Audio Super-Resolution via Noise-Robust Latent Flow Matching
Fei Liu, Yang Ai, Hui-Peng Du +2
Audio super-resolution aims to recover missing high-frequency details from bandwidth-limited low-resolution audio, thereby improving the naturalness and perceptual quality of the r…
ParaGSE: Parallel Generative Speech Enhancement with Group-Vector-Quantization-based Neural Speech Codec
Fei Liu, Yang Ai
Recently, generative speech enhancement has garnered considerable interest; however, existing approaches are hindered by excessive complexity, limited efficiency, and suboptimal sp…
Universal Discrete-Domain Speech Enhancement
Fei Liu, Yang Ai, Ye-Xin Lu +3
In real-world scenarios, speech signals are inevitably corrupted by various types of interference, making speech enhancement (SE) a critical task for robust speech processing. Howe…
Neural Speech Separation with Parallel Amplitude and Phase Spectrum Estimation
Fei Liu, Yang Ai, Zhen-Hua Ling
This paper proposes APSS, a novel neural speech separation model with parallel amplitude and phase spectrum estimation. Unlike most existing speech separation methods, the APSS dis…