First International Conference on Spoken Language Processing (ICSLP 90)
In this paper, a phoneme recognition method using Pairwise Discriminant Time-Delay Neural Networks (PD-TDNNs) is proposed. In conventional approaches to phoneme recognition based on neural networks, it was found that the difference between training data and testing data degrades recognition performance. To overcome this problem, we developed a phoneme recognition method using PD-TDNNs. Each PD-TDNN has the ability to discriminate between two phoneme categories. In this method, phoneme candidates are selected by judging multiple pair discrimination scores, each of which is obtained from the PD-TDNN. We tested this method on a phoneme recognition task for /b,d,g,m,n,N/. Testing on continuous speech using the PD-TDNNs which were trained with the phoneme data in isolated word utterances, we obtained a first candidate recognition rate of 81.6%, and 96.7% for the cumulative recognition rate up to third candidates.
Bibliographic reference. Takami, Jun-Ichi / Sagayama, Shigeki (1990): "Phoneme recognition by pairwise discriminant TDNNs", In ICSLP-1990, 677-680.