5 papers · 1 filter
DisSR: Disentangling Speech Representation for Degradation-Prior Guided Cross-Domain Speech Restoration
Ziqi Liang, Zhijun Jia, Chang Liu +3
Previous speech restoration (SR) primarily focuses on single-task speech restoration (SSR), which cannot address general speech restoration problems. Training specific SSR models f…
CycleFlow: Leveraging Cycle Consistency in Flow Matching for Speaker Style Adaptation
Ziqi Liang, Xulong Zhang, Chang Liu +3
Voice Conversion (VC) aims to convert the style of a source speaker, such as timbre and pitch, to the style of any target speaker while preserving the linguistic content. However,…
EfficientASR: Speech Recognition Network Compression via Attention Redundancy and Chunk-Level FFN Optimization
Jianzong Wang, Ziqi Liang, Xulong Zhang +2
In recent years, Transformer networks have shown remarkable performance in speech recognition tasks. However, their deployment poses challenges due to high computational and storag…
EAD-VC: Enhancing Speech Auto-Disentanglement for Voice Conversion with IFUB Estimator and Joint Text-Guided Consistent Learning
Ziqi Liang, Jianzong Wang, Xulong Zhang +3
Using unsupervised learning to disentangle speech into content, rhythm, pitch, and timbre for voice conversion has become a hot research topic. Existing works generally take into a…
EM-TTS: Efficiently Trained Low-Resource Mongolian Lightweight Text-to-Speech
Ziqi Liang, Haoxiang Shi, Jiawei Wang +1
Recently, deep learning-based Text-to-Speech (TTS) systems have achieved high-quality speech synthesis results. Recurrent neural networks have become a standard modeling technique…