”“I have hat,” and “I have bat,” then the first two tokens of the three sentences are likely to be correct since they are the same among all beam candidates. The inconsistency on the last token shows that: 1) this token may need correction, and 2...
Microsoft has carried out a series of work on the FastCorrect model, including FastCorrect 1, FastCorrect 2 and FastCorrect 3. Each job addresses a different problem and scenario. FastCorrect 1 was published at the NeurIPS 2021 conference. It is mainly based on the prior knowledge of the pr...
Explore computer vision in Microsoft Azure Topic Computer vision is an area of artificial intelligence (AI) in which software systems are designed to perceive the world visually, though cameras, images, and video. There are multiple specific types of computer vision problem that AI engineers and da...
3 , Tie-Yan Liu 21 University of Science and Technology of China, 2 Microsoft Research Asia3 Microsoft Azure Speech, 4 Tsinghua University1 lyc123go@mail.ustc.edu.cn,xiangyangli@ustc.edu.cn2 {xuta,ruiwa,taoqin,tyliu}@microsoft.com3 {linczhu,liwenjie,linqul,edlin}@microsoft.com4 j-.....
shows that: 1) this token may need correction, and 2) the pronunciation of the ground-truth token may end with “æt”. The voting effect can be utilized to boost ASR correction by helping the model detect the error token and giving clues about the pronunciation of ...