|Enhancing Low-Quality Voice Recordings Using Disentangled Channel Factor And Neural Waveform Model
|Haoyu Li, Yang Ai, Junichi Yamagishi
|Efficient Neural Architecture Search For End-To-End Speech Recognition Via Straight-Through Gradients
|Huahuan Zheng, Keyu An, Zhijian Ou
|VIRAAL: Virtual Adversarial Active Learning For NLU
|Gregory Senay, Badr Youbi Idrissi, Marine Haziza
|Controllable Emphatic Speech Synthesis based on Forward Attention for Expressive Speech Synthesis
|Liangqi Liu, Jiankun Hu, Zhiyong Wu, Song Yang, Songfan Yang, Jia Jia, Helen Meng
|Look Who's Not Talking
|Youngki Kwon, Hee Soo Heo, Jaesung Huh, Bong-Jin Lee, Joon Son Chung
|Alignment Restricted Streaming Recurrent Neural Network Transducer
|Jay Mahadeokar, Yuan Shangguan, Duc Le, Gil Keren, Hang Su, Thong Le, Ching-feng Yeh, Christian Fuegen, Michael L Seltzer
|Discriminative Neural Clustering For Speaker Diarisation
|Qiujia Li, Florian Kreyssig, Chao Zhang, Phil Woodland
|Acoustic Span Embeddings For Multilingual Query-By-Example Search
|Yushi Hu, Shane Settle, Karen Livescu
The SLT Workshop is a biennial flagship event of IEEE Speech and Language Processing Technical Committee. The 8th IEEE Spoken Language Technology Workshop (SLT 2021) will be held on January 19-22, 2021 in Shenzhen, China.
Deep learning has witnessed great success in spoken language technologies over the last decade. We continue welcoming research work from this area. The main theme for SLT 2021 will be around "Spoken language technologies: deep learning and beyond". Besides deep learning, we also encourage explorative efforts on new paradigms and forward-looking approaches for the advancement of spoken language technologies.
The workshop program will keep the successful format of previous SLTs and will feature invited talks/keynotes, regular papers and special sessions. All papers will be presented as posters. A full social program will provide ample opportunities for discussion, including welcome reception, banquet, lunches, etc.
Topics of interest include, but not limited to, the following,
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