mlsanityData to 14 Oct 2026

Automatic Speaker Independent Dysarthric Speech Intelligibility Assessment System

arXiv 2103.06157 ↗First posted 10 Mar 2021cs.SD cs.AI eess.AScited by 2

Not on the map. Why?

Abstract (arXiv)

Dysarthria is a condition which hampers the ability of an individual to control the muscles that play a major role in speech delivery. The loss of fine control over muscles that assist the movement of lips, vocal chords, tongue and diaphragm results in abnormal speech delivery. One can assess the severity level of dysarthria by analyzing the intelligibility of speech spoken by an individual. Continuous intelligibility assessment helps speech language pathologists not only study the impact of medication but also allows them to plan personalized therapy. It helps the clinicians immensely if the intelligibility assessment system is reliable, automatic, simple for (a) patients to undergo and (b) clinicians to interpret. Lack of availability of dysarthric data has resulted in development of speaker dependent automatic intelligibility assessment systems which requires patients to speak a large number of utterances. In this paper, we propose (a) a cost minimization procedure to select an optimal (small) number of utterances that need to be spoken by the dysarthric patient, (b) four different speaker independent intelligibility assessment systems which require the patient to speak a small number of words, and (c) the assessment score is close to the perceptual score that the Speech Language Pathologist (SLP) can relate to. The need for small number of utterances to be spoken by the patient and the score being relatable to the SLP benefits both the dysarthric patient and the clinician from usability perspective.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 3 of its 65 references that are in the map. First posted on arXiv 10 Mar 2021.

Builds on

3 of 65 references.

References · 3

  1. 2019Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speechcited by 5
  2. 2019Robust Estimation of Hypernasality in Dysarthria with Acoustic Model Likelihood Featurescited by 3
  3. 2020Classification of Huntington Disease using Acoustic and Lexical Featurescited by 1

Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 1.

2 papers.