Subjective Tests and Automatic Sentence Modality Recognition with Recordings of Speech Impaired Children

Abstract

Prosody recognition experiments have been prepared in the Laboratory of Speech Acoustics, in which, among the others, we were searching for the possibilities of the recognition of sentence modalities. Due to our promising results in the sentence modality recognition, we adopted the method for children modality recognition, and looked for the possibility, how it can be used as an automatic feedback in an audio - visual pronunciation teaching and training system. Our goal was to develop a sentence intonation teaching and training system for speech handicapped children, helping them to learn the correct prosodic pronunciation of sentence. HMM models of modality types were built by training the recognizer with a correctly speaking children database. During the present work, a large database was collected from speech impaired children. Subjective tests were carried out with this database of speech impaired children, in order to examine how human listeners are able to categorize the heard recordings of sentence modalities. Then automatic sentence modality recognition experiments were done with the formerly trained HMM models. By the result of the subjective tests, the probability of acceptance of the sentence modality recognizer can be adjusted. Comparing the result of the subjective tests and the results of the automatic sentence modality recognition tests processed on the database of speech impaired children, it is showed that the automatic recognizer classified the recordings more strictly, but not worse. The introduced method could be implemented as a part of a speech teaching system.