3 papers
eess.AS2023
Spike-Triggered Contextual Biasing for End-to-End Mandarin Speech Recognition
Kaixun Huang, Ao Zhang, Binbin Zhang +3
The attention-based deep contextual biasing method has been demonstrated to effectively improve the recognition performance of end-to-end automatic speech recognition (ASR) systems…
eess.AS2022
WeKws: A production first small-footprint end-to-end Keyword Spotting Toolkit
Jie Wang, Menglong Xu, Jingyong Hou +4
Keyword spotting (KWS) enables speech-based user interaction and gradually becomes an indispensable component of smart devices. Recently, end-to-end (E2E) methods have become the m…
cs.CL2017
Empirical Evaluation of Parallel Training Algorithms on Acoustic Modeling
Wenpeng Li, BinBin Zhang, Lei Xie +1
Deep learning models (DLMs) are state-of-the-art techniques in speech recognition. However, training good DLMs can be time consuming especially for production-size models and corpo…