2015/06/06 by Megha Rughani, Rughani, Megha, D. Shivakrishna +1
Computer Science · Medicine · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Sound (cs.SD) #Speech Recognition and Synthesis #Speech and Audio Processing #Voice and Speech Disorders #cs.CL #cs.SD
paper · pdf · doi:10.48550/arxiv.1506.02170
arxiv created 2015/06/06 · openalex publication_date 2015/06/06 · arxiv updated 2015/06/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Dysarthria is malfunctioning of motor speech caused by faintness in the human nervous system. It is characterized by the slurred speech along with physical impairment which restricts their communication and creates the lack of confidence and affects the lifestyle. This paper attempt to increase the efficiency of Automatic Speech Recognition (ASR) system for unimpaired speech signal. It describes state of art of research into improving ASR for speakers with dysarthria by means of incorporated knowledge of their speech production. Hybridized approach for feature extraction and acoustic modelling technique along with evolutionary algorithm is proposed for increasing the efficiency of the overall system. Here number of feature vectors are varied and tested the system performance. It is observed that system performance is boosted by genetic algorithm. System with 16 acoustic features optimized with genetic algorithm has obtained highest recognition rate of 98.28% with training time of 5:30:17.