US 11,790,166 B2
Quality assessment method for automatic annotation of speech data
Jun He, Kunming (CN); Caiqing Zhang, Kunming (CN); Fei Deng, Kunming (CN); Shikai Shen, Kunming (CN); Yifang Zhou, Kunming (CN); and Weihao Yue, Kunming (CN)
Assigned to KUNMING UNIVERSITY, Kunming (CN)
Filed by Kunming University, Kunming (CN)
Filed on Nov. 19, 2021, as Appl. No. 17/530,495.
Claims priority of application No. 202011312501.5 (CN), filed on Nov. 20, 2020.
Prior Publication US 2022/0164531 A1, May 26, 2022
Int. Cl. G06F 40/232 (2020.01); G06F 40/169 (2020.01)
CPC G06F 40/232 (2020.01) [G06F 40/169 (2020.01)] 7 Claims
OG exemplary drawing
 
1. A quality assessment method for automatic annotation of speech data, comprising:
step 1, building a base rule-base of automatically annotated speech data according to quality key indicators, wherein the quality key indicators comprise word error rate WER, sentence error rate SER, bias feature error rate PAR and user feedback error rate CER;
step 2, reading automatically annotated speech data to be detected, and performing quality detection on the automatically annotated speech data to be detected according to the quality key indicators to thereby complete quality measurement;
step 3, updating an automatically annotated speech dataset according to a result of the quality measurement; and
step 4, importing the automatically annotated speech dataset after the updating into the base rule-base;
wherein the quality assessment method for automatic annotation of speech data further comprises: applying the base rule-base including the automatically annotated speech dataset after the updating in promoting a development of ethnic minority speech intelligence.