15 citations · 26 across the 6 of their papers we have counts for
6 papers
Beyond Dry References: Learning Relative Audio Effects Representations via Contrastive Distance Learning
Xinlu Liu, Huibin Lin, Weixing Wei +1
Audio effects (Fx) representation learning plays a key role in intelligent music production, including automatic mixing and Fx style transfer. Existing methods typically rely on dr…
Hodge and Podge: Hybrid Supervised Sound Event Detection with Multi-Hot MixMatch and Composition Consistence Training
Ziqiang Shi, Liu Liu, Huibin Lin +1
In this paper, we propose a method called Hodge and Podge for sound event detection. We demonstrate Hodge and Podge on the dataset of Detection and Classification of Acoustic Scene…
HODGEPODGE: Sound event detection based on ensemble of semi-supervised learning methods
Ziqiang Shi, Liu Liu, Huibin Lin +2
In this paper, we present a method called HODGEPODGE\footnotemark[1] for large-scale detection of sound events using weakly labeled, synthetic, and unlabeled data proposed in the D…
FurcaNet: An end-to-end deep gated convolutional, long short-term memory, deep neural networks for single channel speech separation
Ziqiang Shi, Huibin Lin, Liu Liu +4
Deep gated convolutional networks have been proved to be very effective in single channel speech separation. However current state-of-the-art framework often considers training the…
Is CQT more suitable for monaural speech separation than STFT? an empirical study
Ziqiang Shi, Huibin Lin, Liu Liu +2
Short-time Fourier transform (STFT) is used as the front end of many popular successful monaural speech separation methods, such as deep clustering (DPCL), permutation invariant tr…
A Double Joint Bayesian Approach for J-Vector Based Text-dependent Speaker Verification
Ziqiang Shi, Mengjiao Wang, Liu Liu +2
J-vector has been proved to be very effective in text-dependent speaker verification with short-duration speech. However, the current state-of-the-art back-end classifiers, e.g. jo…