70 citations · 222 across the 40 of their papers we have counts for
8 papers · 1 filter
ImagineNET: Target Speaker Extraction with Intermittent Visual Cue through Embedding Inpainting
Zexu Pan, Wupeng Wang, Marvin Borsdorf +1
The speaker extraction technique seeks to single out the voice of a target speaker from the interfering voices in a speech mixture. Typically an auxiliary reference of the target s…
Speaker recognition with two-step multi-modal deep cleansing
Ruijie Tao, Kong Aik Lee, Zhan Shi +1
Neural network-based speaker recognition has achieved significant improvement in recent years. A robust speaker representation learns meaningful knowledge from both hard and easy s…
Controllable Accented Text-to-Speech Synthesis
Rui Liu, Berrak Sisman, Guanglai Gao +1
Accented text-to-speech (TTS) synthesis seeks to generate speech with an accent (L2) as a variant of the standard version (L1). Accented TTS synthesis is challenging as L2 is diffe…
Predict-and-Update Network: Audio-Visual Speech Recognition Inspired by Human Speech Perception
Jiadong Wang, Xinyuan Qian, Haizhou Li
Audio and visual signals complement each other in human speech perception, so do they in speech recognition. The visual hint is less evident than the acoustic hint, but more robust…
A Hybrid Continuity Loss to Reduce Over-Suppression for Time-domain Target Speaker Extraction
Zexu Pan, Meng Ge, Haizhou Li
The speaker extraction algorithm extracts the target speech from a mixture speech containing interference speech and background noise. The extraction process sometimes over-suppres…
L-SpEx: Localized Target Speaker Extraction
Meng Ge, Chenglin Xu, Longbiao Wang +3
Speaker extraction aims to extract the target speaker's voice from a multi-talker speech mixture given an auxiliary reference utterance. Recent studies show that speaker extraction…
ADD 2022: the First Audio Deep Synthesis Detection Challenge
Jiangyan Yi, Ruibo Fu, Jianhua Tao +17
Audio deepfake detection is an emerging topic, which was included in the ASVspoof 2021. However, the recent shared tasks have not covered many real-life and challenging scenarios.…
Noise-robust voice conversion with domain adversarial training
Hongqiang Du, Lei Xie, Haizhou Li
Voice conversion has made great progress in the past few years under the studio-quality test scenario in terms of speech quality and speaker similarity. However, in real applicatio…