Dysarthria intelligibility assessment in a factor analysis total variability space

Speech technologies are more important every day to assist people with speech disorders. They can help to increase their quality of life or help clinicians to make a diagnosis. In this paper a new methodology based on a total variability subspace modelled by factor analysis is proposed to assess the intelligibility of people with dysarthria. The acoustic information of each recording is efficiently compressed and a Pearson correlation of 0.91 between the vectors in this subspace (iVectors) and the intelligibility is obtained. As acoustic information only perceptual linear prediction features are used. The experiments are conducted on Universal Access Speech database. Also a new error metric to overcome the subjectivity in the intelligibility labels is proposed.

[1]  Elmar Nöth,et al.  Combining Phonological and Acoustic ASR-Free Features for Pathological Speech Intelligibility Assessment , 2011, INTERSPEECH.

[2]  Jean-Pierre Martens,et al.  Automated Intelligibility Assessment of Pathological Speech Using Phonological Features , 2009, EURASIP J. Adv. Signal Process..

[3]  A. Aronson,et al.  Motor Speech Disorders , 2014 .

[4]  Raymond D. Kent.  The MIT Encyclopedia of Communication Disorders , 2003 .

[5]  Janet M. Baker,et al.  The Design for the Wall Street Journal-based CSR Corpus , 1992, HLT.

[6]  H. A. Leeper,et al.  Dysarthric speech: a comparison of computerized speech recognition and listener intelligibility. , 1997, Journal of rehabilitation research and development.

[7]  Phil D. Green,et al.  Revisiting dysarthria assessment intelligibility metrics , 2004, INTERSPEECH.

[8]  M. Bodt,et al.  Intelligibility as a linear combination of dimensions in dysarthric speech. , 2002 .

[9]  P. Enderby.  Disorders of communication: dysarthria. , 2013, Handbook of clinical neurology.

[10]  Phil D. Green,et al.  Automatic speech recognition with sparse training data for dysarthric speakers , 2003, INTERSPEECH.

[11]  Nasser M. Nasrabadi,et al.  Pattern Recognition and Machine Learning , 2006, Technometrics.

[12]  Fraser Shein,et al.  Characterization of atypical vocal source excitation, temporal dynamics and prosody for objective measurement of dysarthric word intelligibility , 2012, Speech Commun..

[13]  Jon Gunderson,et al.  UNIVERSAL ACCESS : PRELIMINARY EXPERIMENTS IN DYSARTHRIC SPEECH RECOGNITION Harsh , 2008 .

[14]  Tiago H. Falk,et al.  Automated Dysarthria Severity Classification for Improved Objective Intelligibility Assessment of Spastic Dysarthric Speech , 2012, INTERSPEECH.

[15]  Douglas A. Reynolds,et al.  Robust text-independent speaker identification using Gaussian mixture speaker models , 1995, IEEE Trans. Speech Audio Process..

[16]  P. Enderby,et al.  Frenchay Dysarthria Assessment , 1983 .

[17]  Patrick Kenny,et al.  Front-End Factor Analysis for Speaker Verification , 2011, IEEE Transactions on Audio, Speech, and Language Processing.

[18]  H Hermansky,et al.  Perceptual linear predictive (PLP) analysis of speech. , 1990, The Journal of the Acoustical Society of America.

[19]  J. Martens,et al.  Speech technology-based assessment of phoneme intelligibility in dysarthria. , 2009, International journal of language & communication disorders.

[20]  Thomas S. Huang,et al.  Dysarthric speech database for universal access research , 2008, INTERSPEECH.

[21]  Tiago H. Falk,et al.  Quantifying perturbations in temporal dynamics for automated assessment of spastic dysarthric speech intelligibility , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[22]  Heidi Christensen,et al.  A comparative study of adaptive, automatic recognition of disordered speech , 2012, INTERSPEECH.

[23]  Elmar Nöth,et al.  Automatic intelligibility assessment of speakers after laryngeal cancer by means of acoustic modeling. , 2012, Journal of voice : official journal of the Voice Foundation.

[24]  Bernhard Schölkopf,et al.  A tutorial on support vector regression , 2004, Stat. Comput..

[25]  Carmichael Jn,et al.  Introducing objective acoustic metrics for the frenchay dysarthria assessment procedure. , 2007 .