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eess.AS2025
TripleC Learning and Lightweight Speech Enhancement for Multi-Condition Target Speech Extraction
Ziling Huang
In our recent work, we proposed Lightweight Speech Enhancement Guided Target Speech Extraction (LGTSE) and demonstrated its effectiveness in multi-speaker-plus-noise scenarios. How…
eess.AS2025
Lightweight speech enhancement guided target speech extraction in noisy multi-speaker scenarios
Ziling Huang, Junnan Wu, Lichun Fan +4
Target speech extraction (TSE) has achieved strong performance in relatively simple conditions such as one-speaker-plus-noise and two-speaker mixtures, but its performance remains…
eess.AS2025
SEF-PNet: Speaker Encoder-Free Personalized Speech Enhancement with Local and Global Contexts Aggregation
Ziling Huang, Haixin Guan, Haoran Wei +1
Personalized speech enhancement (PSE) methods typically rely on pre-trained speaker verification models or self-designed speaker encoders to extract target speaker clues, guiding t…