音韻検査のための非語の音声認識に有効な特徴量の検討

Developmental dyslexia is a main element of learning disability and its early detection is very important for intervention and reading treatment. A convenient screening test using PC has been published and the answer times in text reading, reversed reading of word and mora skip of word are automatically recorded in the test. However, the correctness determination must be done by tester. In order to automate those test, a speech recognition technology corresponding to a non-word that are non-meaningful words used in an examination is necessary, but in conventional speech recognition, recognition precision for non-words is low. Therefore, while reinforcing the function of conventional speech recognition, the accuracy for non-words to be improved to a level that can be practically used for phoneme examination. In this study, we have tried to improve the accuracy for non-words by incorporating a mechanism to determine non-word correctness into Julius, which is in the public domain and can be modified freely. In addition, six candidates are given as feature quantities of speech, and the trend of the accuracy by the combination is examined. As a result, depending on the target non-word, the accuracy was 75.0% to 95.0%, and the overall average value was 87.5%.