A pairwise discriminant approach to robust phoneme recognition by time-delay neural networks

The authors propose a phoneme recognition method using pairwise discriminant time-delay neural networks (PD-TDNNs) and show its high recognition performance with experimental results for /b, d, g, m, n, N/. They tested this method on a phoneme recognition task for 18 Japanese consonants (/g, d, g, p, t, k, m, n, N, s, sh, h, z, ch, ts, r, w, y/) and considered its basic performance in detail. In tests on continuous speech using PD-TDNNs trained with the 18 consonant phoneme data in isolated word utterances, the authors obtained a first candidate recognition rate of 76.8%, and 92.9% for the cumulative recognition rate up to third candidates