85 citations · 207 across the 20 of their papers we have counts for
5 papers · 1 filter
Continual Learning for Fake Audio Detection
Haoxin Ma, Jiangyan Yi, Jianhua Tao +3
Fake audio attack becomes a major threat to the speaker verification system. Although current detection approaches have achieved promising results on dataset-specific scenarios, th…
FSR: Accelerating the Inference Process of Transducer-Based Models by Applying Fast-Skip Regularization
Zhengkun Tian, Jiangyan Yi, Ye Bai +3
Transducer-based models, such as RNN-Transducer and transformer-transducer, have achieved great success in speech recognition. A typical transducer model decodes the output sequenc…
TSNAT: Two-Step Non-Autoregressvie Transformer Models for Speech Recognition
Zhengkun Tian, Jiangyan Yi, Jianhua Tao +4
The autoregressive (AR) models, such as attention-based encoder-decoder models and RNN-Transducer, have achieved great success in speech recognition. They predict the output sequen…
Half-Truth: A Partially Fake Audio Detection Dataset
Jiangyan Yi, Ye Bai, Jianhua Tao +5
Diverse promising datasets have been designed to hold back the development of fake audio detection, such as ASVspoof databases. However, previous datasets ignore an attacking situa…
Fast End-to-End Speech Recognition via Non-Autoregressive Models and Cross-Modal Knowledge Transferring from BERT
Ye Bai, Jiangyan Yi, Jianhua Tao +3
Attention-based encoder-decoder (AED) models have achieved promising performance in speech recognition. However, because the decoder predicts text tokens (such as characters or wor…