182 citations · 435 across the 38 of their papers we have counts for
7 papers · 1 filter
LA-VocE: Low-SNR Audio-visual Speech Enhancement using Neural Vocoders
Rodrigo Mira, Buye Xu, Jacob Donley +4
Audio-visual speech enhancement aims to extract clean speech from a noisy environment by leveraging not only the audio itself but also the target speaker's lip movements. This appr…
Leveraging Heteroscedastic Uncertainty in Learning Complex Spectral Mapping for Single-channel Speech Enhancement
Kuan-Lin Chen, Daniel D. E. Wong, Ke Tan +3
Most speech enhancement (SE) models learn a point estimate and do not make use of uncertainty estimation in the learning process. In this paper, we show that modeling heteroscedast…
Improving Speech Enhancement through Fine-Grained Speech Characteristics
Muqiao Yang, Joseph Konan, David Bick +3
While deep learning based speech enhancement systems have made rapid progress in improving the quality of speech signals, they can still produce outputs that contain artifacts and…
SAQAM: Spatial Audio Quality Assessment Metric
Pranay Manocha, Anurag Kumar, Buye Xu +4
Audio quality assessment is critical for assessing the perceptual realism of sounds. However, the time and expense of obtaining ''gold standard'' human judgments limit the availabi…
Speech Quality Assessment through MOS using Non-Matching References
Pranay Manocha, Anurag Kumar
Human judgments obtained through Mean Opinion Scores (MOS) are the most reliable way to assess the quality of speech signals. However, several recent attempts to automatically esti…
The impact of removing head movements on audio-visual speech enhancement
Zhiqi Kang, Mostafa Sadeghi, Radu Horaud +3
This paper investigates the impact of head movements on audio-visual speech enhancement (AVSE). Although being a common conversational feature, head movements have been ignored by…