| dc.description.abstract | Abstract
Language is one of the most important communication tool. Recently, patients with articulatory disorders are increasing year by year and causing problems in their communication with other people. Mobile devices, such as smart phone and tablet PC, become more common as the development of technology advances. It would be a great help for patients and speech therapists if we could apply our mobile devices for speech diagnosis and rehabilitation. Therefore, the purpose of this study was to develop an Android-based speech diagnosis and rehabilitation system which could be used to record and compare the speech signals from the normal speaker and the patient with articulation disorder via the user interface. In this user interface, the clinical users could compare these two signals in the forms of speech signal, spectrum, spectrogram, and the fundamental frequency to provide a quantitative analysis for the speech therapist and greater therapeutic effect for patients with articulatory disorders.
In this study, we analyzed and compared speech recordings, including Chinese vowel and consonants, from the previous cooperative hospital with fast Fourier transform, linear predictive coding and other acoustic quantitative methods to provide useful speech-related diagnostic graphic information. Our results showed that clinical users could observe the difference between normal and disordered speech through our research system with differences in the first three formant frequencies for vowel and energy distribution in the spectrograms for consonants. In addition, patients with articulatory disorders could also use our system for self-training and -learning.
In order to evaluate the validity, functionality and usefulness of our system, we compared the results of our system with the Praat system and the visible voice diagnosis and rehabilitation system which was previously developed with Matlab in our lab. In summary, the Android-based speech diagnosis and rehabilitation system could show the differences between normal and disordered speech on the mobile devices. The speech therapists could use our system as a diagnostic and assessment tool in the clinical settings, and provide patients with articulatory disorders a better training and rehabilitation tool. | en_US |