Automatic generation of consonant discrimination rules

This paper proposes a new automatic rule generation approach for rule-based consonant discrimination. A rule unit used here is represented by a conditional branch. All rules are optimally generated for the discrimination of the consonant learning samples. Clear and simple rule description permits immediate evaluation as well as further improvement. This approach is effective for the generation of a large number of complicated rules, which is difficult using the conventional heuristic approach. This paper also shows that a more precise discrimination rule set can be obtained by generating rules depending on the succeeding vowel. The experimental results for 100 Japanese city names spoken by 50 speakers indicate that the consonant discrimination rate is 73.7 % employing the resulting vowel dependent rules.