1 citations · 3 across the 21 of their papers we have counts for
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LuSeeL: Language-queried Binaural Universal Sound Event Extraction and Localization
Zexu Pan, Shengkui Zhao, Yukun Ma +4
Most universal sound extraction algorithms focus on isolating a target sound event from single-channel audio mixtures. However, the real world is three-dimensional, and binaural au…
FD-Bench: A Full-Duplex Benchmarking Pipeline Designed for Full Duplex Spoken Dialogue Systems
Yizhou Peng, Yi-Wen Chao, Dianwen Ng +4
Full-duplex spoken dialogue systems (FDSDS) enable more natural human-machine interactions by allowing real-time user interruptions and backchanneling, compared to traditional SDS…
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…
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…
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…
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…