138 citations · 1.4k across the 89 of their papers we have counts for
16 papers · 1 filter
U-shaped Transformer with Frequency-Band Aware Attention for Speech Enhancement
Yi Li, Yang Sun, Syed Mohsen Naqvi
The state-of-the-art speech enhancement has limited performance in speech estimation accuracy. Recently, in deep learning, the Transformer shows the potential to exploit the long-r…
One to Multiple Mapping Dual Learning: Learning Multiple Sources from One Mixed Signal
Ting Liu, Wenwu Wang, Xiaofei Zhang +2
Single channel blind source separation (SCBSS) refers to separate multiple sources from a mixed signal collected by a single sensor. The existing methods for SCBSS mainly focus on…
Diverse Audio Captioning via Adversarial Training
Xinhao Mei, Xubo Liu, Jianyuan Sun +2
Audio captioning aims at generating natural language descriptions for audio clips automatically. Existing audio captioning models have shown promising improvement in recent years.…
End-to-end translation of human neural activity to speech with a dual-dual generative adversarial network
Yina Guo, Xiaofei Zhang, Zhenying Gong +2
In a recent study of auditory evoked potential (AEP) based brain-computer interface (BCI), it was shown that, with an encoder-decoder framework, it is possible to translate human n…
A Mutual learning framework for Few-shot Sound Event Detection
Dongchao Yang, Helin Wang, Yuexian Zou +2
Although prototypical network (ProtoNet) has proved to be an effective method for few-shot sound event detection, two problems still exist. Firstly, the small-scaled support set is…
ARCA23K: An audio dataset for investigating open-set label noise
Turab Iqbal, Yin Cao, Andrew Bailey +2
The availability of audio data on sound sharing platforms such as Freesound gives users access to large amounts of annotated audio. Utilising such data for training is becoming inc…