Dysarthria

About: Dysarthria is a research topic. Over the lifetime, 2402 publications have been published within this topic receiving 56554 citations.

Relationship between the Maximal Tongue and Lip Strength and Percentage of Correct Consonants and Speech Intelligibility in Dysarthric Adults with Cerebral Palsy

Abstract: The purpose of this study was to identify the relationship between the strength of the tongue/lip strength and speech production for dysarthric adults with cerebral palsy. The maximal tongue and lip strengths of 22 normal adults, 27 dysarthric adults (10 adults with mild dysarthria, 10 adults with moderate dysarthria, and 7 adults with severe dysarthria) were measured with Iowa Oral Performance Instrument (IOPI). The percentage of correct consonants (PCC) and speech intelligibility were calculated from the words and sentences spoken by the subjects. The results of the study are as follows: First, both the maximal tongue and the maximal lip strength differed significantly between the control group and the group with dysarthria. While the group with mild dysarthria did not show meaningful difference in maximal tongue and lip strengths from the control group, the group with moderate and severe dysarthria showed significantly weaker tongue and lip strength than the control group and the group with mild dysarthria. Second, the current study suggests the existence of a significant correlation between the maximal tongue and lip strength and the PCC and speech intelligibility within all subjects with dysarthria. These findings can serve as an effective foundation to diagnose dysarthria quickly and accurately. The results of this study also indicate that in addition to the maximal tongue strength, the maximal lip strength can prove to be an important index in predicting the speech intelligibility of dysarthric adults with cerebral palsy.

Sensorimotor Adaptation of Speech Using Real-time Articulatory Resynthesis

Abstract: Sensorimotor adaptation is an important focus in the study of motor learning for non-disordered speech, but has yet to be studied substantially for speech rehabilitation. Speech adaptation is typically elicited experimentally using LPC resynthesis to modify the sounds that a speaker hears himself producing. This method requires that the participant be able to produce a robust speech-acoustic signal and is therefore not well-suited for talkers with dysarthria. We have developed a novel technique using electromagnetic articulography (EMA) to drive an articulatory synthesizer. The acoustic output of the articulatory synthesizer can be perturbed experimentally to study auditory feedback effects on sensorimotor learning. This work aims to compare sensorimotor adaptation effects using our articulatory resynthesis method with effects from an established, acoustic-only method. Results suggest that the articulatory resynthesis method can elicit speech adaptation, but that the articulatory effects of the two methods differ.

Motor Speech Impairments

Abstract: According to conventional clinical taxonomies for neurological speech and language disorders, the term motor speech impairment comprises the different dysarthria syndromes as well as the syndrome of apraxia of speech (AOS). While the dysarthria syndromes are considered to result from pathologies afflicting the control and execution of speech movements, apraxia of speech is usually ascribed to a dysfunction of speech motor planning or programming functions.

Speech recognition system and unit

Abstract: The invention provides a speech recognition system and unit. The speech recognition system includes an image capturing device capable of capturing images of lips, an oral cavity parameter capturing device capable sensing the change of the tongue position, and a speech recognition device. The speech recognition device can receive and analyze lip shape signals of the image capturing device and tongue distance signals and jaw position signals of the oral cavity parameter capturing device to obtain a voice parameter set. An output unit outputs the voice parameter set. During a speech process of a patient with dysarthria, the speech recognition system can automatically analyze the change of the lip shapes and the tongue of the patient with dysarthria to obtain a voice parameter set corresponding to specific voice materials, and can further perform voice synthesis output according to the voice materials matching the voice parameter set to make the speeches of the patient with dysarthria clearly understood.