Estimation of multi-templates for speech recognition by using spectrum reforming and self-organized clustering

This report proposes a new recognition method of continuous Japanese speech. In order to overcome some difficulties in a large vocabulary recognition system, which requires large calculation cost and memory area, the proposed system only recognizes the single phonemes which are automatically selected from continuous speech. The automatic selection can be realized using a new spectrum reforming technique, i.e., a method which smooths the estimated parameters using a nonlinear filter and a parameter quantization method based on a priori rules. This system can also easily search the optimal template for speech phonemes using the self-organized clustering method. This technique is suitable for optimum estimation of multi-templates for continuous speech recognition.