7 citations · 18 across the 9 of their papers we have counts for
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eess.AS2021★ 7 cited
A Comparative Study on Non-Autoregressive Modelings for Speech-to-Text Generation
Yosuke Higuchi, Nanxin Chen, Yuya Fujita +6
Non-autoregressive (NAR) models simultaneously generate multiple outputs in a sequence, which significantly reduces the inference speed at the cost of accuracy drop compared to aut…
eess.AS2021
Layer Pruning on Demand with Intermediate CTC
Jaesong Lee, Jingu Kang, Shinji Watanabe
Deploying an end-to-end automatic speech recognition (ASR) model on mobile/embedded devices is a challenging task, since the device computational power and energy consumption requi…
eess.AS2021★ 7 cited
Intermediate Loss Regularization for CTC-based Speech Recognition
Jaesong Lee, Shinji Watanabe
We present a simple and efficient auxiliary loss function for automatic speech recognition (ASR) based on the connectionist temporal classification (CTC) objective. The proposed ob…