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20222025
most citedAdaptive Knowledge Distillation between Text and Speech Pre-trained Models

1 citations · 2 across the 12 of their papers we have counts for

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6 papers · 1 filter

eess.AS2025

Online Audio-Visual Autoregressive Speaker Extraction

Zexu Pan, Wupeng Wang, Shengkui Zhao +4

This paper proposes a novel online audio-visual speaker extraction model. In the streaming regime, most studies optimize the audio network only, leaving the visual frontend less ex…

eess.AS2025

Plug-and-Play Co-Occurring Face Attention for Robust Audio-Visual Speaker Extraction

Zexu Pan, Shengkui Zhao, Tingting Wang +4

Audio-visual speaker extraction isolates a target speaker's speech from a mixture speech signal conditioned on a visual cue, typically using the target speaker's face recording. Ho…

eess.AS2024

Emotional Dimension Control in Language Model-Based Text-to-Speech: Spanning a Broad Spectrum of Human Emotions

Kun Zhou, You Zhang, Dianwen Ng +3

Emotional text-to-speech (TTS) systems sturggle to capture the full spectrum of human emotions due to the inherent complexity of emotional expressions and the limited coverage of e…

eess.AS2024

Phonetic Enhanced Language Modeling for Text-to-Speech Synthesis

Kun Zhou, Shengkui Zhao, Yukun Ma +7

Recent language model-based text-to-speech (TTS) frameworks demonstrate scalability and in-context learning capabilities. However, they suffer from robustness issues due to the acc…

eess.AS2023

SPGM: Prioritizing Local Features for enhanced speech separation performance

Jia Qi Yip, Shengkui Zhao, Yukun Ma +8

Dual-path is a popular architecture for speech separation models (e.g. Sepformer) which splits long sequences into overlapping chunks for its intra- and inter-blocks that separatel…

eess.AS2022

Mixed-EVC: Mixed Emotion Synthesis and Control in Voice Conversion

Kun Zhou, Berrak Sisman, Carlos Busso +2

Emotional voice conversion (EVC) traditionally targets the transformation of spoken utterances from one emotional state to another, with previous research mainly focusing on discre…