Re-Talk: Automated Speech Assistance for People with Dysarthria | ||||
| النشرة المعلوماتية في الحاسبات والمعلومات | ||||
| Volume 5, Issue 1 - Serial Number 20230501, January 2023, Page 16-22 PDF (712.18 K) | ||||
| Document Type: المقالة الأصلية | ||||
| DOI: 10.21608/fcihib.2023.188592.1077 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Salma Khaled Ali  ; Aya Mohamed Hassan; Ahmed Mohamed Salah; Donia Wael Mohamed; Muhammed Mustafa; Ensaf Hussein Mohamed
| ||||
| Computer Science, Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt. | ||||
| Abstract | ||||
| Dysarthria is a speech motor disorder where the muscles responsible for speech production, such as in the face, mouth, or respiratory system, have trouble coordinating and controlling themselves. Our research goal is to help individuals with dysarthria communicate effectively. Often, physical conditions make it challenging for them to express their thoughts through writing. Our research introduces an automatic speech assistant solution, consisting of two main parts: speech recognition and auto-correct. The speech recognition component takes the person's distorted speech as input, converts it to text, and then sends it to the auto-correct module to fix any mistakes or unclear words. We tested our model on both English and Arabic datasets. The English dataset showed a 50% Word Error Rate (WER) which was reduced to 40% after using the auto-correct module. Our results outperformed previous studies by 4.5%. However, the WER on the Arabic dataset was 80% which is not a satisfactory result, due to the limited size of the Egyptian Dialect Dysarthric Speech (EDDS) database. | ||||
| Keywords | ||||
| DSR; B-LSTM; CNN-LSTM; UASpeech Database; Auto Correction | ||||
| References | ||||
|
| ||||
|
Statistics Article View: 463 PDF Download: 393 |
||||
