Comparing Humans and Automatic Speech Recognition Systems in Recognizing Dysarthric Speech

Abstract. Speech is a complex process that requires control and coordination of articulation, breathing, voicing, and prosody. Dysarthria is a manifestation of an inability to control and coordinate one or more of these aspects, which results in poorly articulated and hardly intelligible speech. Hence individuals with dysarthria are rarely understood by human listeners. In this paper, we compare and evaluate how well dysarthric speech can be recognized by an automatic speech recognition system (ASR) and na¨ıve adult human listeners. The results show that despite the encouraging performance of ASR systems, and contrary to the claims in other studies, on average human listeners perform better in recognizing single-word dysarthric speech. In particular, the mean word recognition accuracy of speaker-adapted monophone ASR systems on stimuli produced by six dysarthric speakers is 68.39% while the mean percentage correct response of 14 na¨ıve human listeners on the same speech is 79.78% a...

• Type: Journal
• Year: 2011
• Where: AI
• Authors: Kinfe Tadesse Mengistu, Frank Rudzicz
• Keywords: AI 2011, Artificial Intelligence, Automatic Speech Recognition, Speech Recognition System, Word Recognition Accuracy