activity
20192022
most citedLeveraging Phone Mask Training for Phonetic-Reduction-Robust E2E Uyghur Speech Recognition

9 citations · 22 across the 7 of their papers we have counts for

collaborators

7 papers

cs.SD20229 cited

Leveraging Phone Mask Training for Phonetic-Reduction-Robust E2E Uyghur Speech Recognition

Guodong Ma, Pengfei Hu, Jian Kang +2

In Uyghur speech, consonant and vowel reduction are often encountered, especially in spontaneous speech with high speech rate, which will cause a degradation of speech recognition…

cs.SD2021

VRM-Phase I VKW system description of long-short video customizable keyword wakeup challenge

Yougen Yuan, Zhiqiang Lv, Shen Huang +1

Keyword wakeup technology has always been a research hotspot in speech processing, but many related works were done on different datasets. We organized a Chinese long-short video k…

cs.CL20216 cited

Stacked Acoustic-and-Textual Encoding: Integrating the Pre-trained Models into Speech Translation Encoders

Chen Xu, Bojie Hu, Yanyang Li +5

Encoder pre-training is promising in end-to-end Speech Translation (ST), given the fact that speech-to-translation data is scarce. But ST encoders are not simple instances of Autom…

cs.CL2020

Dynamic Curriculum Learning for Low-Resource Neural Machine Translation

Chen Xu, Bojie Hu, Yufan Jiang +6

Large amounts of data has made neural machine translation (NMT) a big success in recent years. But it is still a challenge if we train these models on small-scale corpora. In this…

cs.CL20204 cited

Code-switching pre-training for neural machine translation

Zhen Yang, Bojie Hu, Ambyera Han +2

This paper proposes a new pre-training method, called Code-Switching Pre-training (CSP for short) for Neural Machine Translation (NMT). Unlike traditional pre-training method which…

cs.CV2020

A Multi-oriented Chinese Keyword Spotter Guided by Text Line Detection

Pei Xu, Shan Huang, Hongzhen Wang +3

Chinese keyword spotting is a challenging task as there is no visual blank for Chinese words. Different from English words which are split naturally by visual blanks, Chinese words…