Search Results for author:
Found 6 papers, 4 papers with code
Rethinking Transfer and Auxiliary Learning for Improving Audio Captioning Transformer
In this paper, we propose a simple transfer learning scheme that maintains input patch sizes, unlike previous methods, to avoid input discrepancies.
Ranked #5 on
Audio captioning
on AudioCaps
MetricGAN-OKD: Multi-Metric Optimization of MetricGAN via Online Knowledge Distillation for Speech Enhancement
In speech enhancement, MetricGAN-based approaches reduce the discrepancy between the $L_p$ loss and evaluation metrics by utilizing a non-differentiable evaluation metric as the objective function.
Ranked #7 on
Speech Enhancement
on VoiceBank + DEMAND
AD-YOLO: You Look Only Once in Training Multiple Sound Event Localization and Detection
Hence, the format enables the model to handle the polyphony problem, regardless of the number of sound overlaps.
TriAAN-VC: Triple Adaptive Attention Normalization for Any-to-Any Voice Conversion
The existing methods do not simultaneously satisfy the above two aspects of VC, and their conversion outputs suffer from a trade-off problem between maintaining source contents and target characteristics.
Multi-View Attention Transfer for Efficient Speech Enhancement
In this study, we propose multi-view attention transfer (MV-AT), a feature-based distillation, to obtain efficient speech enhancement models in the time domain.
Ranked #14 on
Speech Enhancement
on VoiceBank + DEMAND
MANNER: Multi-view Attention Network for Noise Erasure
In the field of speech enhancement, time domain methods have difficulties in achieving both high performance and efficiency.
Ranked #8 on
Speech Enhancement
on VoiceBank + DEMAND
