Literature DB >> 27908075

The relationship between perceptual disturbances in dysarthric speech and automatic speech recognition performance.

Ming Tu1, Alan Wisler2, Visar Berisha1, Julie M Liss1.   

Abstract

State-of-the-art automatic speech recognition (ASR) engines perform well on healthy speech; however recent studies show that their performance on dysarthric speech is highly variable. This is because of the acoustic variability associated with the different dysarthria subtypes. This paper aims to develop a better understanding of how perceptual disturbances in dysarthric speech relate to ASR performance. Accurate ratings of a representative set of 32 dysarthric speakers along different perceptual dimensions are obtained and the performance of a representative ASR algorithm on the same set of speakers is analyzed. This work explores the relationship between these ratings and ASR performance and reveals that ASR performance can be predicted from perceptual disturbances in dysarthric speech with articulatory precision contributing the most to the prediction followed by prosody.

Entities:  

Mesh:

Year:  2016        PMID: 27908075      PMCID: PMC6909999          DOI: 10.1121/1.4967208

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  10 in total

1.  Intelligibility of laryngectomees' substitute speech: automatic speech recognition and subjective rating.

Authors:  Maria Schuster; Tino Haderlein; Elmar Nöth; Jörg Lohscheller; Ulrich Eysholdt; Frank Rosanowski
Journal:  Eur Arch Otorhinolaryngol       Date:  2005-07-07       Impact factor: 2.503

2.  Automatic assessment of vowel space area.

Authors:  Steven Sandoval; Visar Berisha; Rene L Utianski; Julie M Liss; Andreas Spanias
Journal:  J Acoust Soc Am       Date:  2013-11       Impact factor: 1.840

3.  Characterizing the distribution of the quadrilateral vowel space area.

Authors:  Visar Berisha; Steven Sandoval; Rene Utianski; Julie Liss; Andreas Spanias
Journal:  J Acoust Soc Am       Date:  2014-01       Impact factor: 1.840

4.  Modeling Pathological Speech Perception From Data With Similarity Labels.

Authors:  Visar Berisha; Julie Liss; Steven Sandoval; Rene Utianski; Andreas Spanias
Journal:  Proc IEEE Int Conf Acoust Speech Signal Process       Date:  2014-05

Review 5.  Perceptual learning of dysarthric speech: a review of experimental studies.

Authors:  Stephanie A Borrie; Megan J McAuliffe; Julie M Liss
Journal:  J Speech Lang Hear Res       Date:  2011-12-22       Impact factor: 2.297

6.  Convex weighting criteria for speaking rate estimation.

Authors:  Yishan Jiao; Visar Berisha; Ming Tu; Julie Liss
Journal:  IEEE/ACM Trans Audio Speech Lang Process       Date:  2015-09

7.  Quantifying speech rhythm abnormalities in the dysarthrias.

Authors:  Julie M Liss; Laurence White; Sven L Mattys; Kaitlin Lansford; Andrew J Lotto; Stephanie M Spitzer; John N Caviness
Journal:  J Speech Lang Hear Res       Date:  2009-08-28       Impact factor: 2.297

8.  Intelligibility as a linear combination of dimensions in dysarthric speech.

Authors:  Marc S De Bodt; Huici Maria E Hernández-Díaz; Paul H Van De Heyning
Journal:  J Commun Disord       Date:  2002 May-Jun       Impact factor: 2.288

9.  Listener agreement for auditory-perceptual ratings of dysarthria.

Authors:  Kate Bunton; Raymond D Kent; Joseph R Duffy; John C Rosenbek; Jane F Kent
Journal:  J Speech Lang Hear Res       Date:  2007-12       Impact factor: 2.297

10.  The effects of familiarization on intelligibility and lexical segmentation in hypokinetic and ataxic dysarthria.

Authors:  Julie M Liss; Stephanie M Spitzer; John N Caviness; Charles Adler
Journal:  J Acoust Soc Am       Date:  2002-12       Impact factor: 1.840

  10 in total
  1 in total

1.  Automatic Speech Recognition in Noise for Parkinson's Disease: A Pilot Study.

Authors:  Alireza Goudarzi; Gemma Moya-Galé
Journal:  Front Artif Intell       Date:  2021-12-22
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.