US 11,721,325 B1
Method for generating learning data for speech recognition error detection
Seongmin Park, Seoul (KR); Dongchan Shin, Seoul (KR); Sangyoun Paik, Gwangmyeong-si (KR); Subong Choi, Seoul (KR); Alena Kazakova, Siheung-si (KR); and Jihwa Lee, Seoul (KR)
Assigned to ActionPower Corp., Seoul (KR)
Filed by ActionPower Corp., Seoul (KR)
Filed on Jul. 27, 2022, as Appl. No. 17/875,112.
Claims priority of application No. 10-2022-0071409 (KR), filed on Jun. 13, 2022.
Int. Cl. G10L 15/06 (2013.01); G06F 40/284 (2020.01)
CPC G10L 15/063 (2013.01) [G06F 40/284 (2020.01)] 10 Claims
OG exemplary drawing
 
1. A method for generating data, the method performed by a computing device, the method comprising:
segmenting text data generated based on speech information into a token unit;
generating a first feature vector based on the text data segmented into the token unit, and generating a first label vector corresponding to the generated first feature vector;
generating a second feature vector and a second label vector by performing mix-up for each of the generated first feature vector and the generated first label vector;
determining a prediction label by inputting the generated second feature vector into a neural network model, and
training the neural network model based on the determined prediction label and the second label vector.