A high-accuracy ASR technique based on correlational weight analysis for elderly users

This paper proposes a robust template based on the previously proposed ECWRT (enhanced cross word reference template) for template-based ASR, by using correlational weight adjusting method to improve robustness against elderly speech variation named CWCWRT. This work addresses two vital issues: such as outlier rejection in training set and elimination of unwanted utterances which usually happen by the elderly people. Consequently, two main steps are investigated in this paper, firstly, correlational analyzing, and secondly, weight adjusting. For experiments, the corpus is built by 30 commands in Mandarin and English collected from three elderly (age 62±3 years) and three adults (age 22±2 years) having total 30 utterances for each of them. Two types of platforms including PC and GPCE063A embedded platform are conducted, both inside test and outside test are also applied. The results show that the average recognition rate for inside testis 97% in PC simulation and 90% in the embedded platform. The outside test results are 93% and 87% in two platforms respectively. The related and previous works including cross word reference template (CWRT) and ECWRT are also compared the comparison exhibit that the proposed CWCWRT gives higher robustness and accuracy than two baselines.