A Numerical Speech Recognition by Parameters Estimated from the Data on the Estimated Plane and a Neural Network
Il-Hong Choi, Seung-Kwan Jang, Tae-Hoo Cha, Ung-Se Choi, Chang‐Seok Kim · The Journal of the Acoustical Society of Korea · 1996
This paper was proposed the recognition method by using parameters which was estimated from the data on the estimated plane and a neural network. After the LPC estimated in each frame algorithm was mapped to the estimated plane by the optimum feature mapping function, we estimated the C-LPC and the maximum and minimum value and 3 divided power from the mapping data on the estimated plane. As a result of the experiment of the speech recognition that those parameters were applied to the input of a neural network, it was found that those parameters estimated from the estimated plane have the features of the original speech for a change in the time scale and that the recongnition rate by the proposed methods was 96.3 percent.